Top Data Scientist Jobs Openings in 2025

false

About the TeamThe Strategic Finance team at OpenAI plays a critical role in shaping the company’s long-term trajectory. We partner closely with Product, Engineering, and Go-to-Market teams to inform high-stakes decisions through rigorous data science and economic modeling.As part of our expanding Data Science function, we’re building a best-in-class forecasting capability to drive real-time, data-driven decision-making across user growth, revenue, compute infrastructure, and more.We are developing a scalable forecasting platform to help us understand and anticipate business dynamics in an increasingly complex, usage-based world. Our models are foundational to planning, pricing, operational efficiency, and growth strategy — supporting key investment decisions and unlocking OpenAI’s full potential.About the RoleWe’re looking for a hands-on technical leader to build and lead a small but mighty team of applied data scientists and ML engineers to develop forecasting capabilities and platforms from the ground up.Your team will be responsible for building and scaling robust, interpretable, and production-ready forecasting systems. These models will power critical business decisions by predicting core metrics such as DAU/WAU, revenue, compute consumption, and profitability.You will work closely with Strategic Finance leaders to integrate these scalable forecasting capabilities into their operational rhythms and collaborate with the Growth team to forecast key KPIs.This is a highly cross-functional role that requires technical excellence, strong product intuition, and business acumen. You’ll collaborate with various partners to operationalize forecasting insights, influence company-wide strategy, and build foundational forecasting capabilities at OpenAI.This role is based in San Francisco, CA. We follow a hybrid work model of three days in the office per week and offer relocation assistance to new employees.In this role, you will:Build and manage a world-class team of applied data scientists and ML engineers to develop forecasting platforms at scale.Design and own the roadmap for the forecasting platform in partnership with cross-functional stakeholders.Collaborate closely with Strategic Finance teams to ensure forecasts are well integrated into planning processes, and executive decision-making.Work closely with cross-functional partners to help them adopt scientific, automated forecasting solutions.Own the end-to-end modeling lifecycle, including scoping, feature engineering, model development and prototyping, experimentation, deployment, monitoring, and explainability.Research and evaluate emerging tools and techniques in the forecasting space.Translate technical outputs into business-aligned recommendations and decision frameworks.You might thrive in this role if you have:Extensive experience building production-ready models for time series applications.Proven track record of building adjustable and explainable forecast models for multiple planning cycles.10+ years of applied data science & engineering experience, with deep hands-on expertise in forecasting and predictive modeling.Demonstrated experience with model monitoring, debugging, and long-term maintenance in production environments.Excellent communication and storytelling skills — able to simplify complexity and influence executive stakeholders.Team leadership experience with a track record of building high-performing, engaged teams.An advanced degree (MS or PhD) in a quantitative field (e.g., Statistics, Computer Science, Economics, Operations Research).A self-directed, intellectually curious mindset and comfort leading ambiguous projects from 0→1.The ability to thrive in a dynamic environment — flexible, resourceful, and willing to do what it takes to succeed.Experience building or scaling forecasting platforms in a high-growth company.A passion for AI and a strong perspective on how machine learning should inform strategic decisions in fast-moving environments.Experience building or scaling forecasting platforms in a high-growth company.A passion for AI and a strong perspective on how machine learning should inform strategic decisions in fast-moving environments. Bonus if you have:Experience building or scaling forecasting platforms in a high-growth company.A passion for AI and a strong perspective on how machine learning should inform strategic decisions in fast-moving environments.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

false

Please read this firstWe know that this job title says we are looking for a Quantum Computing Researcher. In practice, this role is not that at all.We are using this title because people with backgrounds like yours tend to have the kind of brain that does exceptionally well here, even though the work itself does not fit neatly into an existing category.Maincode builds frontier AI models end to end. We design the models, run the infrastructure, and train on data we source and shape ourselves. What we have been calling a “data scientist” does not actually exist in the market in the form we need. The work we are doing is frontier work. It changes continuously as models, methods, and training regimes evolve, and there is no stable body of prior experience that reliably predicts success. This role is best understood internally as a Signal Engineer.What this role actually isThe real work here is not analytics, dashboards, or big data engineering.It is about how AI models learn, and specifically how the quality, composition, timing, and structure of input signal shapes learning outcomes across the full training lifecycle, from early pre training through mid training, post training, supervised fine tuning, and reinforcement learning.The analogy we use internally is a fuels engineer for a race car. The engine matters, but performance is ultimately unlocked by obsessing over the fuel. What goes in, how it is blended, when it is introduced, and how it changes under different conditions.What you would actually doYou would be responsible for designing, sourcing, shaping, and evaluating input signal at scale so that models learn faster, learn better, and generalize more effectively.This includes:Working deeply with raw and synthetic dataDesigning new datasets and signal mixturesIterating on input distributions and formatsUnderstanding how small changes in signal affect training behaviorThinking across stages of training, not in isolationTreating data as a dynamic, evolving system rather than a static assetThis is not about knowing the right answer up front. It is about immersion, experimentation, and developing intuition through long feedback loops.The kind of person who does well hereSuccess in this role is driven almost entirely by cognitive traits and working style, not prior AI experience.People who tend to thrive here:Have extreme attention to detail and care deeply about precisionAre comfortable with long arcs of repetitive, detailed workEnjoy staring at complex, noisy information until structure emergesAre excited by tuning, blending, and calibrating inputsHave high stamina and patienceLearn new technical domains very quickly when given dense materialGet intrinsic satisfaction from incremental improvement and deep understandingThese are people who do not get bored easily. They metabolize boredom into insight. They are depth driven rather than novelty driven.We explicitly do not require prior experience with large language models or modern AI training. No one meaningfully has that experience yet. What matters is learning gradient, range, and willingness to throw yourself into the problem space.How you would workYou would spend your time inside computational environments and technical tooling.You do not need to identify as a software engineer, but you should be comfortable:Working directly with data through scripts, notebooks, and experimental pipelinesModifying existing systems and building small utilities to explore questionsUsing code as a tool for thinking, testing, and refinementThe goal is speed of learning and depth of understanding, not polish.Backgrounds that often fit wellRather than advertising this role directly, we look for people in fields that reward signal sensitivity, precision, and long horizon reasoning.We expect to see strong candidates from areas such as:Actuarial scienceForensic accounting or forensic financeQuantum computingQuantitative risk modelingApplied statistics and signal processingEconometricsOperations researchWe also see excellent fits from applied mathematics, computational physics, systems engineering, bioinformatics, reliability engineering, and similar disciplines.Many people in these fields are constrained by conservative or slow moving industries and are actively looking for something more dynamic, even if they do not yet realize there is a place for them in frontier AI.How we interviewWe are explicitly hiring for learning gradient, not recall.Our process is designed to:See how quickly you build a mental model of an unfamiliar systemUnderstand how you reason about signal, feedback, and failure modesObserve how deeply you engage with input quality as a leverLearn whether you enjoy the work itself, not just the outcomeCorrectness matters less than depth, curiosity, and systems intuition.The core messageWe are offering a path for people who love signal, precision, and deep work to apply that obsession to frontier AI.This role is not about having the right background. It is about having the right brain, the right stamina, and the desire to become excellent at something that does not quite have a name yet.

false

Please read this firstWe know that this job title says we are looking for an Actuary. In practice, this role is not that at all.We are using this title because people with backgrounds like yours tend to have the kind of brain that does exceptionally well here, even though the work itself does not fit neatly into an existing category.Maincode builds frontier AI models end to end. We design the models, run the infrastructure, and train on data we source and shape ourselves. What we have been calling a “data scientist” does not actually exist in the market in the form we need. The work we are doing is frontier work. It changes continuously as models, methods, and training regimes evolve, and there is no stable body of prior experience that reliably predicts success. This role is best understood internally as a Signal Engineer.What this role actually isThe real work here is not analytics, dashboards, or big data engineering.It is about how AI models learn, and specifically how the quality, composition, timing, and structure of input signal shapes learning outcomes across the full training lifecycle, from early pre training through mid training, post training, supervised fine tuning, and reinforcement learning.The analogy we use internally is a fuels engineer for a race car. The engine matters, but performance is ultimately unlocked by obsessing over the fuel. What goes in, how it is blended, when it is introduced, and how it changes under different conditions.What you would actually doYou would be responsible for designing, sourcing, shaping, and evaluating input signal at scale so that models learn faster, learn better, and generalize more effectively.This includes:Working deeply with raw and synthetic dataDesigning new datasets and signal mixturesIterating on input distributions and formatsUnderstanding how small changes in signal affect training behaviorThinking across stages of training, not in isolationTreating data as a dynamic, evolving system rather than a static assetThis is not about knowing the right answer up front. It is about immersion, experimentation, and developing intuition through long feedback loops.The kind of person who does well hereSuccess in this role is driven almost entirely by cognitive traits and working style, not prior AI experience.People who tend to thrive here:Have extreme attention to detail and care deeply about precisionAre comfortable with long arcs of repetitive, detailed workEnjoy staring at complex, noisy information until structure emergesAre excited by tuning, blending, and calibrating inputsHave high stamina and patienceLearn new technical domains very quickly when given dense materialGet intrinsic satisfaction from incremental improvement and deep understandingThese are people who do not get bored easily. They metabolize boredom into insight. They are depth driven rather than novelty driven.We explicitly do not require prior experience with large language models or modern AI training. No one meaningfully has that experience yet. What matters is learning gradient, range, and willingness to throw yourself into the problem space.How you would workYou would spend your time inside computational environments and technical tooling.You do not need to identify as a software engineer, but you should be comfortable:Working directly with data through scripts, notebooks, and experimental pipelinesModifying existing systems and building small utilities to explore questionsUsing code as a tool for thinking, testing, and refinementThe goal is speed of learning and depth of understanding, not polish.Backgrounds that often fit wellRather than advertising this role directly, we look for people in fields that reward signal sensitivity, precision, and long horizon reasoning.We expect to see strong candidates from areas such as:Actuarial scienceForensic accounting or forensic financeQuantum computingQuantitative risk modelingApplied statistics and signal processingEconometricsOperations researchWe also see excellent fits from applied mathematics, computational physics, systems engineering, bioinformatics, reliability engineering, and similar disciplines.Many people in these fields are constrained by conservative or slow moving industries and are actively looking for something more dynamic, even if they do not yet realize there is a place for them in frontier AI.How we interviewWe are explicitly hiring for learning gradient, not recall.Our process is designed to:See how quickly you build a mental model of an unfamiliar systemUnderstand how you reason about signal, feedback, and failure modesObserve how deeply you engage with input quality as a leverLearn whether you enjoy the work itself, not just the outcomeCorrectness matters less than depth, curiosity, and systems intuition.The core messageWe are offering a path for people who love signal, precision, and deep work to apply that obsession to frontier AI.This role is not about having the right background. It is about having the right brain, the right stamina, and the desire to become excellent at something that does not quite have a name yet.

false

About LMArenaLMArena is the open platform for evaluating how AI models perform in the real world. Created by researchers from UC Berkeley’s SkyLab, our mission is to measure and advance the frontier of AI for real-world use. Millions of people use LMArena each month to explore how frontier systems perform — and we use our community’s feedback to build transparent, rigorous, and human-centered model evaluations. Leading enterprises and AI labs rely on our evaluations to understand real-world reliability, alignment, and impact. Our leaderboards are the gold standard for AI performance — trusted by leaders across the AI community and shaping the global conversation on model reliability and progress. We’re a team of researchers, engineers, academics, and builders from places like UC Berkeley, Google, Stanford, DeepMind, and Discord. We seek truth, move fast, and value craftsmanship, curiosity, and impact over hierarchy. We’re building a company where thoughtful, curious people from all backgrounds can do their best work. Everyone on our team is a deep expert in their field — our office radiates excellence, energy, and focus.About the RoleAs a Senior Data Scientist you’ll explore and reason about the data that powers millions of AI evaluations each week. You’ll generate and test hypotheses, identify causal relationships, and uncover insights that help us understand how frontier models behave in the real world. You’ll collaborate with ML researchers and engineers to design experiments, analyze large-scale datasets, and build statistical frameworks that improve the reliability and interpretability of our AI evaluation systems.You’llExplore and analyze large, complex datasets to uncover patterns, biases, and causal relationships in model behavior and system performance.Formulate hypotheses about data quality, evaluation outcomes, and model performance — then design experiments to validate or refute them.Build reproducible analysis pipelines using Python, Pandas, NumPy, and Spark to process and interrogate large-scale data.Partner with ML researchers and engineers to design metrics and analyses that evaluate how models perform across domains, prompts, and tasks.Develop causal reasoning frameworks and statistical methods that help explain why models behave as they do — not just how well they perform.Communicate insights (for example, via blog posts) clearly to technical and non-technical partners, informing both research direction and infrastructure improvements.You’ll have6+ years of experience in data science, ML analytics, or applied research, preferably in AI, ML, or large-scale data environments.Strong proficiency in Python, with deep experience in Pandas, NumPy, and distributed frameworks like Spark.Expertise in statistical modeling, causal inference, and experimental design.Experience reasoning about data distributions, sample quality, and the effects of data distribution shifts.Strong communication skills and the ability to collaborate closely with ML researchers and engineers.(Bonus) Background in AI model evaluation.(Bonus) Experience working with LLM outputs (for example, LLM-as-a-judge), embeddings, or other large-scale model artifacts.(Bonus) Experience with A/B testing.What we offerThe cash compensation for this position has not yet been finalized. Actual compensation will depend on job-related knowledge, skills, experience, and candidate location.Competitive salary and meaningful equityComprehensive healthcare coverage (medical, dental, vision)The opportunity to work on cutting-edge AI with a small, mission-driven teamA culture that values transparency, trust, and community impactWhat we offerWe offer competitive compensation and equity aligned to the markets where our team members are based. The base salary range will depend on the candidate’s permanent work location.Comprehensive health and wellness benefits, including medical, dental, vision, and additional support programs.The opportunity to work on cutting-edge AI with a small, mission-driven teamA culture that values transparency, trust, and community impactCome help build the space where anyone can explore and help shape the future of AI.LMArena provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity, or gender expression. We are committed to a diverse and inclusive workforce and welcome people from all backgrounds, experiences, perspectives, and abilities.

false

Role & ReportingTitle: Senior Data ScientistHiring Manager: Marco, Data LeadLocation: Monday - Thursday in our Chancery Lane office (London), Friday remote.Compensation: £100-£140k base plus equity. About UsSince launching in May 2024 we’ve grown to $20 million in ARR.We’re building an AI executive assistant that handles emails, scheduling and follow-up, freeing people in client-facing roles to focus on their customers. What We ValueWe hire small numbers of exceptional people who want ownership and autonomy. You’ll be expected to work with urgency and intensity, but you’ll also gain responsibility quickly and see your work have a direct impact.What You’ll DoIn short, you’ll own Fyxer AI’s data science capabilities — you’ll set the roadmap for high-impact business areas like marketing and retention, implement scalable solutions, and ensure stakeholders use data to make confident commercial decisions.You’llBuild and refine predictive models on multi‑channel customer and usage data to drive product and marketing decisions. Collaborate with engineering, marketing, sales and product teams to define KPIs, experiment with new algorithms and surface actionable insights that drive impact. Maintain data infrastructure (BigQuery, dbt, Fivetran) and ensure data quality for reporting and self‑service analytics. Develop a culture of data-driven decision making and proactively suggest improvements to tools, processes and architecture. About YouYou use first principles to really understand the problem and build solutions that have real business impact You get frustrated just dealing with tickets and want to partner with businesses Experience working at a fast paced early-stage tech company (<100 people). Expert in SQL and comfortable with Python/R; experience building and deploying machine-learning models. Strong ability to transform messy data into production-ready datasets and communicate technical findings to non-technical stakeholders.People that thrive at FyxerYou want to build and have impact from the ground up. You want to have unreasonable ownership of your own world You work hard, with intensity everyday & move incredibly quickly You always challenge the systems you’re in to be better

false

As a Data Scientist, you will play a pivotal role in aligning our AI solutions with the unique needs of our manufacturing clients. Your primary responsibility will be to lead the development of state-of-the-art AI applications that tackle complex industry challenges, driving innovation and enhancing productivity.We are seeking an experienced data scientist capable of extracting valuable insights from manufacturing data. Your tasks will include mining, interpreting, and analyzing customer data to discover hidden opportunities and fully leverage its potential. Also, your role will involve direct interaction with customers to grasp their challenges and to understand their unique data characteristics. By closely engaging with customers, you will develop tailored data models and tools to meet their specific needs. Additionally, you will collaborate with our cross-functional teams to conceive, design, and develop innovative AI products for manufacturing by identifying new product features based on the understanding of customer data.Join a team of passionate innovators dedicated to revolutionizing the future of manufacturing. Take the lead in pioneering cutting-edge AI initiatives that directly impact real-world outcomes. Collaborate with a diverse and talented group of experts where your ideas will be highly valued, and your contributions will drive Gauss Labs towards becoming the global leader in industrial AI innovation.ResponsibilitiesDesign and implement customized AI solutions for manufacturingAnalyze manufacturing data to uncover opportunities and develop AI modelsCollaborate with customers to understand their requirements and deliver clear, data-driven solutionsWork closely with our internal teams to ensure solutions are feasible, scalable, and aligned with product strategyPresent findings to both technical and non-technical stakeholdersBasic QualificationsBS/MS in Engineering, Science, or a related field2+ years of experience leading AI or data science projects in the semiconductor industry or another manufacturing fieldStrong problem-solving skills and customer-focused mindsetProficiency in data science tools: Python and SQLAbility to work independently and as part of a teamTravel domestically to customer sites as needed (up to 20% of working hours)Fluency in KoreanPreferred QualificationsMS in Computer Science, Data Science, or related fieldExperience in predictive modeling and cloud platforms (e.g., AWS, Azure, Google Cloud)Excellent communication skills, with the ability to simplify complex technical conceptsFluency in English[Interview process]Application review - Phone interview - Virtual onsite interview - VP interview/Core Value interview - CEO interview

false

Role & ReportingTitle: Lead Data ScientistHiring Manager: Marco, Data LeadLocation: Monday - Thursday in our Chancery Lane office (London), Friday remote.Compensation: £140,000 - £170,000 base plus equity. About UsSince launching in May 2024 we’ve grown to $20 million in ARR.We’re building an AI executive assistant that handles emails, scheduling and follow-up, freeing people in client-facing roles to focus on their customers. What We ValueWe hire small numbers of exceptional people who want ownership and autonomy. You’ll be expected to work with urgency and intensity, but you’ll also gain responsibility quickly and see your work have a direct impact.What You’ll DoIn short, you’ll own Fyxer AI’s data science capabilities — you’ll set the roadmap for high-impact business areas like marketing and retention, implement scalable solutions, and ensure stakeholders use data to make confident commercial decisions.You’llBuild and refine predictive models on multi‑channel customer and usage data to drive product and marketing decisions. Collaborate with engineering, marketing, sales and product teams to define KPIs, experiment with new algorithms and surface actionable insights that drive impact. Maintain data infrastructure (BigQuery, dbt, Fivetran) and ensure data quality for reporting and self‑service analytics. Develop a culture of data-driven decision making and proactively suggest improvements to tools, processes and architecture. About YouYou use first principles to really understand the problem and build solutions that have real business impact You get frustrated just dealing with tickets and want to partner with businesses Experience working at a fast paced early-stage tech company (<100 people). Expert in SQL and comfortable with Python/R; experience building and deploying machine-learning models. Strong ability to transform messy data into production-ready datasets and communicate technical findings to non-technical stakeholders.People that thrive at FyxerYou want to build and have impact from the ground up. You want to have unreasonable ownership of your own world You work hard, with intensity everyday & move incredibly quickly You always challenge the systems you’re in to be better

false

Machinify is a leading healthcare intelligence company with expertise across the payment continuum, delivering unmatched value, transparency, and efficiency to health plan clients across the country. Deployed by over 60 health plans, including many of the top 20, and representing more than 160 million lives, Machinify brings together a fully configurable and content-rich, AI-powered platform along with best-in-class expertise. We’re constantly reimagining what’s possible in our industry, creating disruptively simple, powerfully clear ways to maximize financial outcomes and drive down healthcare costs. We are seeking a Principal Data Scientist. This role will be responsible for the overall leadership and management of the data science team at Machinify, and requires a deep technical background, strong leadership skills, and the ability to drive innovation and excellence in a fast-paced environment. Reporting to the Chief Data Scientist, the Director of Data Science will collaborate closely with other leaders to align engineering efforts with the company's strategic goals.  What you will do:Provide direction and guidance to a team of Senior and Staff Data Scientists, enabling them to do their best workCollaborate with the leadership team to define key technical and business metrics and objectivesTranslate objectives into internal team priorities and assignmentsDrive sprints and work with cross-functional stakeholders to appropriately prioritize various initiatives to improve customer metricsHire, mentor and develop team membersFoster a culture of innovation, collaboration, and continuous improvementCommunicate technical concepts and strategies to technical and non-technical stakeholders effectivelyOwn the success of various models on the field by continuously monitoring KPI’s and initiating projects to improve quality.  What you bring:Degree in Computer Science, Engineering, or a related field10+ years of data science experience, with at least 5 years in a leadership role, including a leadership role at a start-up. Proven track record of managing data teams and delivering complex, high-impact products from concept to deploymentStrong knowledge of data privacy regulations and best practices in data securityExceptional team management abilities, with experience in building and leading high-performing teamsAbility to think strategically and execute methodicallyAbility to drive change and inspire a distributed teamStrong problem-solving skills and a data-driven mindsetAbility to communicate effectively, collaborating with diverse groups to solve complex problemsYou embrace challenges with optimism and a balanced, and bring a business-oriented approach to product developmentYou prioritize customer impact, ensuring your work significantly advances our product valueWhat we offer:A flexible and trusting environment where you'll feel empowered to do your best work.Work from anywhere in the US! Our team is distributed and most of us work from home.Hardworking and supportive colleagues, and a leadership team that understands the importance of recruiting and retaining top talent.Incredible medical, vision, and dental benefits for employees & their families.Competitive salary and equity, 401(k) sponsorship.Equal Employment Opportunity at MachinifyMachinify is committed to hiring talented and qualified individuals with diverse backgrounds for all of its positions. Machinify believes that the gathering and celebration of unique backgrounds, qualities, and cultures enriches the workplace. See our Candidate Privacy Notice at: https://www.machinify.com/candidate-privacy-notice/

false

Multiverse is the upskilling platform for AI and Tech adoption.We have partnered with 1,500+ companies to deliver a new kind of learning that's transforming today’s workforce.Our upskilling apprenticeships are designed for people of any age and career stage to build critical AI, data, and tech skills. Our learners have driven $2bn+ ROI for their employers, using the skills they’ve learned to improve productivity and measurable performance.In June 2022, we announced a $220 million Series D funding round co-led by StepStone Group, Lightspeed Venture Partners and General Catalyst. With a post-money valuation of $1.7bn, the round makes us the UK’s first EdTech unicorn.But we aren’t stopping there. With a strong operational footprint and 800+ employees, we have ambitious plans to continue scaling. We’re building a world where tech skills unlock people’s potential and output. Join Multiverse and power our mission to equip the workforce to win in the AI era.As a Senior Data Scientist, you will play a pivotal role in steering our Data Science team towards achieving strategic objectives. Your expertise will guide collaborative efforts in product and backend services alike, whilst collaborating with product experts, engineers and other stakeholders from across the organization.You'll leverage your advanced analytical skills and understanding of AI and machine learning to drive impactful insights and foster innovative solutions. This dynamic role demands a balance of creativity and analytical rigor within a fast-paced environment, ensuring quick learning and iteration based on user feedback.What you’ll focus on:Translate complex stakeholder queries and hypotheses into actionable analyses, experiments and AI/ML model requirements.Develop a comprehensive understanding of our data lineage and sources, addressing and mitigating sampling and analytical biases.Oversee the productionization of analyses and models, ensuring their seamless operation at scale by adhering to software engineering best practices.Drive targeted exploration of our data landscape, ideating and implementing innovative ways to use data for enhancing user engagement on our productsBuild out our knowledge graph capability for underpinning AI/ML models and agentic workflowsProactively monitor and refine analyses and models, optimizing effectiveness and efficiency while minimizing biases and operational challenges.Evaluate and validate scalable methodologies for data collection and processing, ensuring robust practices are in place.Communicate actionable insights to stakeholders at all levels, bridging the gap between technical concepts and business objectives.What we’re looking for:Required:5+ years of data science/machine learning experience, with a proven track record in leading complex data projects.Extensive experience in deploying supervised/unsupervised machine learning algorithms and AI tools into production, delivering scalable and effective solutions.Strong proficiency in Python and key libraries commonly used in machine learning (e.g., NumPy, Pandas, Scikit-Learn, PyTorch, Langchain).Advanced working knowledge of SQLExperience with GitHub for version control.Demonstrated experience productionising ML models and analytic outputs within cloud environments (e.g., AWS, Azure).Understanding of best practices in data protection and information security.A tenacious, curious, and pragmatic approach to problem solving, focusing on creating usable, scalable outputs.Exceptional attention to detail and a strong analytical mindset.A growth-oriented attitude and a passion for continuous learning and professional development.A commitment to Multiverse’s mission and values.Non-Required (But Desirable):Familiarity with the education/skills sectorUnderstanding of the semantic web, knowledge graphs and/or network analyticsDirect experience with CI/CD practices (e.g., GitHub Actions).Knowledge of infrastructure as code tools (e.g., Terraform).An advanced degree in a numerical, engineering or related discipline.BenefitsTime off - 27 days holiday, plus 7 additional days off: 1 life event day, 2 volunteer days and 4 company-wide wellbeing days and 8 bank holidays per yearHealth & Wellness- private medical Insurance with Bupa, a medical cashback scheme, life insurance, gym membership & wellness resources through Gympass and access to Spill - all in one mental health supportHybrid work offering - and the opportunity to take part in our work-from-anywhere schemeTeam fun - weekly socials, company wide events and office snacksOur commitment to Diversity, Equity and InclusionWe’re an equal opportunities employer. And proud of it. Every applicant and employee is afforded the same opportunities regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. This will never change. Read our Equality, Diversity & Inclusion policy here.Right to WorkDo you have the right to work in the UK? Unfortunately, at this time we cannot offer sponsorship for this role and we cannot consider overseas applications.SafeguardingAll posts in Multiverse involve some degree of responsibility for safeguarding. Successful applicants are required to complete a Disclosure Form from the Disclosure and Barring Service ("DBS") for the position. Failure to declare any convictions (that are not subject to DBS filtering) may disqualify a candidate for appointment or result in summary dismissal if the discrepancy comes to light subsequently.

false

About MercorMercor is at the intersection of labor markets and AI research. We partner with leading AI labs and enterprises to provide the human intelligence essential to AI development.Our vast talent network trains frontier AI models in the same way teachers teach students: by sharing knowledge, experience, and context that can't be captured in code alone. Today, more than 30,000 experts in our network collectively earn over $1.5 million a day.Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society.Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our new San Francisco headquarters.About the RoleAs a Data Science Intern at Mercor, you’ll join a fast-moving, metrics-driven engineering team that powers critical decisions across the company. You’ll analyze data that directly impacts ranking, hiring efficiency, candidate experience, and revenue. From day one, you’ll work with real datasets, ship insights used by product and engineering, and prototype models that improve how we match talent to AI companies.You’ll work closely with engineers, PMs, and leadership, designing experiments, evaluating LLM-powered systems, and building the foundations of data integrity and visibility across the platform. You’ll move quickly while maintaining a high bar for analytical rigor, clarity, and statistical correctness.At the end of the process, you’ll be team-matched to where you can have the most impact, on one of the following:Talent platform analytics – improving match quality, ranking, time-to-hire, and marketplace efficiency through experimentation and modeling.Applied AI/human data insights – partnering with leading AI labs (OpenAI, Anthropic, Google) to design evaluation rubrics, run human-in-the-loop studies, and understand how experts shape post-training data for frontier models.What You’ll Work OnAs an intern, you’ll take on projects such as:Defining north-star metrics and feature-level KPIs for ranking, interview analytics, and payouts systems.Designing and running A/B tests and quasi-experiments; translating results into product decisions within days.Building dashboards and lightweight data models that empower teams to self-serve insights.Instrumenting events with engineers and improving data quality, observability, and latency.Prototyping models (from baselines to gradient boosting) to improve matching and scoring systems.Evaluating LLM-powered agents through rubric design, human-in-the-loop experiments, and guardrail canary testing.What We’re Looking ForPursuing a degree in a quantitative field (graduating 2025–2027).Strong fundamentals in statistics, SQL, and Python.Experience with experiment design, causal reasoning, and data analysis.Ability to communicate clearly with engineers, product managers, and leadership.Curiosity about LLM evaluation, retrieval, ranking, or marketplace dynamics (a plus).Excited to work in person and thrive in a fast-paced environment.Nice-to-haves: experience with dbt, dashboarding tools, recommendation/search metrics, or LLM/agent evaluation.Why MercorImpact: Your work powers how AI labs train and deploy their modelsLearning: Get early exposure to frontier AI research and engineeringGrowth: Work with a high-velocity team where interns ship to productionBenefitsCompetitive internship stipend.Mentorship from experienced engineers.Work on real, high-impact projects.$1K monthly stipend for mealsFree Equinox membershipTeam events and offsites.Potential full-time return offer.

false

  The Opportunity As a Data Scientist at Otter.ai, you will be a key player within our Product Development organization. You will leverage your advanced data analytics skills and deep understanding of our products and market to drive strategic decision-making, optimize engagement and monetization strategies, and accelerate product adoption. Your work will significantly enhance customer experiences and contribute to our business success. If you are passionate about using data to drive business growth and want to be part of a team shaping the future of conversations, we invite you to apply and help us achieve our mission of making conversations more valuable. Your Impact Collaborate with Product teams to understand business objectives and challenges, translating them into data-driven insights and recommendations. Develop and implement predictive models, analytical tools, and methodologies to analyze product usage and customer behaviors. Analyze large datasets to generate actionable insights that guide the development and optimization of engagement and monetization strategies. Design and Execute experiments to test hypotheses and measure the effectiveness of various features, product experiences and strategies. Partner with cross-functional teams, including Product Management and Engineering, to integrate data-driven insights into our products and services, driving continuous improvement and innovation. Present findings and recommendations to key stakeholders, including executives, to inform strategic decision-making and shape the company’s Product roadmaps. Collaborate with Data Engineers to ensure data quality, accessibility, and reliability for analysis purposes. Stay current with industry trends, emerging technologies, and best practices in data science, machine learning, and AI to drive innovation and competitiveness. We're Looking for Someone Who 3+ years as a Data Scientist, in a software technology or AI-driven company. Proficiency in SQL for querying large datasets, and expertise in Python and R for data manipulation, analysis, and visualization. Strong background in data analysis, statistical modeling, and other data science techniques. Familiarity with B2B SaaS business models. Excellent ability to translate complex findings into actionable insights for non-technical stakeholders. Proven ability to work effectively in cross-functional teams and manage multiple projects simultaneously. Strong problem-solving skills and the ability to thrive in a fast-paced, dynamic start-up environment. About Otter.ai  We are in the business of shaping the future of work. Our mission is to make conversations more valuable. With over 1B meetings transcribed, Otter.ai is the world’s leading tool for meeting transcription, summarization, and collaboration. Using artificial intelligence, Otter generates real-time automated meeting notes, summaries, and other insights from in-person and virtual meetings - turning meetings into accessible, collaborative, and actionable data that can be shared across teams and organizations. The company is backed by early investors in Google, DeepMind, Zoom, and Tesla. Otter.ai is an equal opportunity employer. We proudly celebrate diversity and are committed to building an inclusive and accessible workplace. We provide reasonable accommodations for qualified applicants throughout the hiring process.  Accessibility & Accommodations  Otter.ai is committed to providing reasonable accommodations for candidates with disabilities in our hiring process.  If you need assistance or an accommodation during any stage of the recruitment process, please contact hr@otter.ai at least 3 business days before your interview. *Otter.ai does not accept unsolicited resumes from 3rd party recruitment agencies without a written agreement in place for permanent placements. Any resume or other candidate information submitted outside of established candidate submission guidelines (including through our website or via email to any Otter.ai employee) and without a written agreement otherwise will be deemed to be our sole property, and no fee will be paid should we hire the candidate. Salary range Salary Range: $155,000 to $185,000 USD per year. This salary range represents the low and high end of the estimated salary range for this position. The actual base salary offered for the role is dependent based on several factors. Our base salary is just one component of our comprehensive total rewards package.

false

About the TeamOpenAI’s User Operations organization is building the data and intelligence layer behind AI-assisted operations — the systems that decide when automation should help users, when humans should step in, and how both improve over time. Our flagship platform is transforming customer support into a model for “agent-first” operations across OpenAI.About the RoleAs a Data Scientist on User Operations, you’ll design the models, metrics, and experimentation frameworks that power OpenAI’s human-AI collaboration loop. You’ll build systems that measure quality, optimize automation, and turn operational data into insights that improve product and user experience at scale. You’ll partner closely with Support Automation Engineering, Product, and Data Engineering to ensure our data systems are production-grade, trusted, and impactful.This role is based in San Francisco or New York City. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees.Why it mattersEvery conversation users have with OpenAI products produces signals about how humans and AI interact. User Ops Data Science turns those signals into insights that shape how we support users today and design agentic systems for tomorrow. This is a unique opportunity to help define how AI collaboration at scale is measured and improved inside OpenAI.In this role, you will:Build and own metrics, classifiers, and data pipelines that determine automation eligibility, effectiveness, and guardrails.Design and evaluate experiments that quantify the impact of automation and AI systems on user outcomes like resolution quality and satisfaction.Develop predictive and statistical models that improve how OpenAI’s support systems automate, measure, and learn from user interactions.Partner with engineering and product teams to create feedback loops that continuously improve our AI agents and knowledge systems.Translate complex data into clear, actionable insights for leadership and cross-functional stakeholders.Develop and socialize dashboards, applications, and other ways of enabling the team and company to answer product data questions in a self-serve wayContribute to establishing data science standards and best practices in an AI-native operations environment.Partner with other data scientists across the company to share knowledge and continually synthesize learnings across the organizationYou might thrive in this role if you have:10+ years of experience in data science roles within product or technology organizations.Expertise in statistics and causal inference, applied in both experimentation and observational causal inference studies.Expert-level SQL and proficiency in Python for analytics, modeling, and experimentation.Proven experience designing and interpreting experiments and making statistically sound recommendations.Experience building data systems or pipelines that power production workflows or ML-based decisioning.Experience developing and extracting insights from business intelligence tools, such as Mode, Tableau, and Looker.Strategic and impact-driven mindset, capable of translating complex business problems into actionable frameworks.Ability to build relationships with diverse stakeholders and cultivate strong partnerships.Strong communication skills, including the ability to bridge technical and non-technical stakeholders and collaborate across various functions to ensure business impact.Ability to operate effectively in a fast-moving, ambiguous environment with limited structure.Strong communication skills and the ability to translate complex data into stories for non-technical partners.Nice-to-haves:Familiarity with large language models or AI-assisted operations platforms.Experience in operational automation or customer support analytics.Background in experimentation infrastructure or human-AI interaction systems.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

false

Who are Heidi?Heidi is building an AI Care Partner that supports clinicians every step of the way, from documentation to delivery of care.We exist to double healthcare’s capacity while keeping care deeply human. In 18 months, Heidi has returned more than 18 million hours to clinicians and supported over 73 million patient visits. Today, more than two million patient visits each week are powered by Heidi across 116 countries and over 110 languages.Founded by clinicians, Heidi brings together clinicians, engineers, designers, scientists, creatives, and mathematicians, working with a shared purpose: to strengthen the human connection at the heart of healthcare.Backed by nearly $100 million in total funding, Heidi is expanding across the USA, UK, Canada, and Europe, partnering with major health systems including the NHS, Beth Israel Lahey Health, MaineGeneral, and Monash Health, among others.We move quickly where it matters and stay grounded in what’s proven, shaping healthcare’s next era. Ready for the challenge?The RoleAs a Data Scientist (AI) on Heidi’s Model Team, you’ll sit at the intersection of AI engineering and data science. In the short term, you’ll partner closely with our AI Engineering team to strengthen the foundations of our data pipelines, analytics, experimentation frameworks, and reporting systems. Over time, this role will evolve into a hands-on contributor in AI/LLM model work—spanning fine-tuning, deployment, personalization, and applied research.This is a unique opportunity for someone who is currently a Data Scientist in Australia or New Zealand, who feels limited by purely analytical challenges and wants to transition into a more technically demanding role that blends engineering rigor with cutting-edge AI innovation. You’ll grow with the team, expanding from data-centric responsibilities into world-class applied AI science.What you’ll do:Experimentation: Collaborate with engineers and product teams to design, implement, and analyze online A/B tests to measure product impact.Analytics & Reporting: Design dashboards, run analyses, and provide clear reporting to inform product and research decisions.Model Fine-Tuning: Gain hands-on experience with large language models by applying fine-tuning techniques (e.g., supervised fine-tuning, parameter-efficient methods) to improve model performance in healthcare-specific tasks.Model Deployment: Support the engineering team in deploying models into production environments, ensuring scalability, reliability, and integration with our clinical workflows.Model Personalisation: Explore approaches for adapting models to specific user needs, such as personalization, domain adaptation, and context-aware inference to enhance clinician productivity and patient care.Collaboration: Partner with data, engineering, product, and medical knowledge teams to align data and model work with Heidi’s mission in healthcare AI.Continuous Learning: Stay up-to-date with emerging AI and ML research, and grow your expertise from data-focused tasks to advanced model science.What we will look for:A background as a Data Scientist (or similar role) with strong skills in Python, SQL, and modern data tooling.Demonstrated experience in data analysis, experimentation (A/B testing), and building dashboards or reporting systems.Solid programming and software engineering skills: ability to write clean, efficient, and maintainable code that can scale into production systems.Good understanding of large language models (LLMs) and transformer architectures—you know how they work under the hood and are motivated to deepen this knowledge further.An interest and motivation to deepen technical expertise in AI/ML—particularly in areas like model fine-tuning, deployment, and personalization.A solid foundation in statistics, probability, and data-driven decision-making.Strong problem-solving skills with the ability to move from vague questions to well-structured experiments and insights.Curiosity, adaptability, and a growth mindset: you’re eager to bridge the gap between data science and AI engineering.Bonus:Experience with machine learning workflows (e.g., training or evaluating models, working with ML pipelines).Familiarity with deep learning frameworks (PyTorch or TensorFlow).Prior exposure to healthcare data or applications.What do we believe in?We create unconventional solutions to difficult problems and we build them fast. We want you to set impossible goals and make them happen, think landing a rocket but the medical version.You'll be surrounded by a world-class team of engineers, medicos and designers to do your best work, inspired by our shared beliefs:We will stop at nothing to improve patient care across the world.We design user experiences for joy and ship them fast.We make decisions in a flat hierarchy that prioritizes the truth over rank.We provide the resources for people to succeed and give them the freedom to do it.Why you will flourish with us 🚀?Flexible hybrid working environment, with 3 days in the office.Additional paid day off for your birthday and wellness daysSpecial corporate rates at Anytime Fitness in Melbourne, Sydney tbc.A generous personal development budget of $500 per annumLearn from some of the best engineers and creatives, joining a diverse teamBecome an owner, with shares (equity) in the company, if Heidi wins, we all winThe rare chance to create a global impact as you immerse yourself in one of Australia’s leading healthtech startupsIf you have an impact quickly, the opportunity to fast track your startup career!Help us reimagine primary care and change the face of healthcare in Australia and then around the world.

false

About xAI xAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All engineers are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.About the Role As an AI Tutor - Economics, you will be instrumental in enhancing the capabilities of our cutting-edge technologies by providing high-quality input and labels using specialized software. Your role involves collaborating closely with our technical team to support the training of new AI tasks, ensuring the implementation of innovative initiatives. You'll contribute to refining annotation tools and selecting complex problems from advanced economics domains, with a focus on macroeconomic forecasting, microeconomic incentives, and behavioral experiments. This position demands a dynamic approach to learning and adapting in a fast-paced environment, where your ability to interpret and execute tasks based on evolving instructions is crucial. AI Tutor’s Role in Advancing xAI’s Mission As an AI Tutor, you will play an essential role in advancing xAI's mission by supporting the training and refinement of xAI’s AI models. AI Tutors teach our AI models about how people interact and react, as well as how people approach issues and discussions in economics. To accomplish this, AI Tutors will actively participate in gathering or providing data, such as text, voice, and video data, sometimes providing annotations, recording audio, or participating in video sessions. We seek individuals who are comfortable and eager to engage in these activities as a fundamental part of the role, ensuring a strong alignment with xAI’s goals and objectives to innovate. Scope An AI Tutor will provide services that include labeling and annotating data in text, voice, and video formats to support AI model training. At times, this may involve recording audio or video sessions, and tutors are expected to be comfortable with these tasks as they are fundamental to the role. Such data is a job requirement to advance xAI’s mission, and AI Tutors acknowledge that all work is done for hire and owned by xAI. Responsibilities Use proprietary software applications to provide input/labels on defined projects. Support and ensure the delivery of high-quality curated data. Play a pivotal role in supporting and contributing to the training of new tasks, working closely with the technical staff to ensure the successful development and implementation of cutting-edge initiatives/technologies. Interact with the technical staff to help improve the design of efficient annotation tools. Choose problems from economics fields that align with your expertise, focusing on areas like macroeconomics, microeconomics, and behavioral economics.  Regularly interpret, analyze, and execute tasks based on given instructions. Key Qualifications Must possess a PhD in Economics or related field Proficiency in reading and writing, both in informal and professional English. Outstanding communication, interpersonal, analytical, and organizational capabilities. Solid reading comprehension skills combined with the capacity to exercise autonomous judgment even when presented with limited data/material. Strong passion for and commitment to technological advancements and innovation in economics. Preferred Qualifications Possesses experience with at least one publication in a reputable economics journal or outlet. Teaching experience as a professor. Location & Other Expectations This position is based in Palo Alto, CA, or fully remote. The Palo Alto option is an in-office role requiring 5 days per week; remote positions require strong self-motivation. If you are based in the US, please note we are unable to hire in the states of Wyoming and Illinois at this time. We are unable to provide visa sponsorship. Team members are expected to work from 9:00am - 5:30pm PST for the first two weeks of training and 9:00am - 5:30pm in their own timezone thereafter. For those who will be working from a personal device, please note your computer must be a Chromebook, Mac with MacOS 11.0 or later, or Windows 10 or later. You must own and have reliable access to a smartphone. Compensation $45/hour - $100/hour The posted pay range is intended for U.S.-based candidates and depends on factors including relevant experience, skills, education, geographic location, and qualifications. For international candidates, our recruiting team can provide an estimated pay range for your location. Benefits: Hourly pay is just one part of our total rewards package at xAI. Specific benefits vary by country, depending on your country of residence you may have access to medical benefits. We do not offer benefits for part-time roles.xAI is an equal opportunity employer. California Consumer Privacy Act (CCPA) Notice

false

About the TeamThe Strategic Finance team at OpenAI plays a critical role in shaping the company’s long-term trajectory. We partner closely with Product, Engineering, and Go-to-Market teams to inform high-stakes decisions through rigorous data science and economic modeling.As part of our expanding Data Science function, we’re building a best-in-class forecasting capability to drive real-time, data-driven decision-making across user growth, revenue, compute infrastructure, and more.We are developing a scalable forecasting platform to help us understand and anticipate business dynamics in an increasingly complex, usage-based world. Our models are foundational to planning, pricing, operational efficiency, and growth strategy — supporting key investment decisions and unlocking OpenAI’s full potential.About the RoleWe’re looking for a hands-on technical leader to build and lead a small but mighty team of applied data scientists and ML engineers to develop forecasting capabilities and platforms from the ground up.Your team will be responsible for building and scaling robust, interpretable, and production-ready forecasting systems. These models will power critical business decisions by predicting core metrics such as DAU/WAU, revenue, compute consumption, and profitability.You will work closely with Strategic Finance leaders to integrate these scalable forecasting capabilities into their operational rhythms and collaborate with the Growth team to forecast key KPIs.This is a highly cross-functional role that requires technical excellence, strong product intuition, and business acumen. You’ll collaborate with various partners to operationalize forecasting insights, influence company-wide strategy, and build foundational forecasting capabilities at OpenAI.This role is based in San Francisco, CA. We follow a hybrid work model of three days in the office per week and offer relocation assistance to new employees.In this role, you will:Build and manage a world-class team of applied data scientists and ML engineers to develop forecasting platforms at scale.Design and own the roadmap for the forecasting platform in partnership with cross-functional stakeholders.Collaborate closely with Strategic Finance teams to ensure forecasts are well integrated into planning processes, and executive decision-making.Work closely with cross-functional partners to help them adopt scientific, automated forecasting solutions.Own the end-to-end modeling lifecycle, including scoping, feature engineering, model development and prototyping, experimentation, deployment, monitoring, and explainability.Research and evaluate emerging tools and techniques in the forecasting space.Translate technical outputs into business-aligned recommendations and decision frameworks.You might thrive in this role if you have:Extensive experience building production-ready models for time series applications.Proven track record of building adjustable and explainable forecast models for multiple planning cycles.10+ years of applied data science & engineering experience, with deep hands-on expertise in forecasting and predictive modeling.Demonstrated experience with model monitoring, debugging, and long-term maintenance in production environments.Excellent communication and storytelling skills — able to simplify complexity and influence executive stakeholders.Team leadership experience with a track record of building high-performing, engaged teams.An advanced degree (MS or PhD) in a quantitative field (e.g., Statistics, Computer Science, Economics, Operations Research).A self-directed, intellectually curious mindset and comfort leading ambiguous projects from 0→1.The ability to thrive in a dynamic environment — flexible, resourceful, and willing to do what it takes to succeed.Bonus if you have:Experience building or scaling forecasting platforms in a high-growth company.A passion for AI and a strong perspective on how machine learning should inform strategic decisions in fast-moving environments.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

true

About xAI xAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All engineers are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.About the Role As an AI Tutor - Economics, you will be instrumental in enhancing the capabilities of our cutting-edge technologies by providing high-quality input and labels using specialized software. Your role involves collaborating closely with our technical team to support the training of new AI tasks, ensuring the implementation of innovative initiatives. You'll contribute to refining annotation tools and selecting complex problems from advanced economics domains, with a focus on macroeconomic forecasting, microeconomic incentives, and behavioral experiments. This position demands a dynamic approach to learning and adapting in a fast-paced environment, where your ability to interpret and execute tasks based on evolving instructions is crucial. AI Tutor’s Role in Advancing xAI’s Mission As an AI Tutor, you will play an essential role in advancing xAI's mission by supporting the training and refinement of xAI’s AI models. AI Tutors teach our AI models about how people interact and react, as well as how people approach issues and discussions in economics. To accomplish this, AI Tutors will actively participate in gathering or providing data, such as text, voice, and video data, sometimes providing annotations, recording audio, or participating in video sessions. We seek individuals who are comfortable and eager to engage in these activities as a fundamental part of the role, ensuring a strong alignment with xAI’s goals and objectives to innovate. Scope An AI Tutor will provide services that include labeling and annotating data in text, voice, and video formats to support AI model training. At times, this may involve recording audio or video sessions, and tutors are expected to be comfortable with these tasks as they are fundamental to the role. Such data is a job requirement to advance xAI’s mission, and AI Tutors acknowledge that all work is done for hire and owned by xAI. Responsibilities Use proprietary software applications to provide input/labels on defined projects. Support and ensure the delivery of high-quality curated data. Play a pivotal role in supporting and contributing to the training of new tasks, working closely with the technical staff to ensure the successful development and implementation of cutting-edge initiatives/technologies. Interact with the technical staff to help improve the design of efficient annotation tools. Choose problems from economics fields that align with your expertise, focusing on areas like macroeconomics, microeconomics, and behavioral economics.  Regularly interpret, analyze, and execute tasks based on given instructions. Key Qualifications Must possess a PhD in Economics or related field Proficiency in reading and writing, both in informal and professional English. Outstanding communication, interpersonal, analytical, and organizational capabilities. Solid reading comprehension skills combined with the capacity to exercise autonomous judgment even when presented with limited data/material. Strong passion for and commitment to technological advancements and innovation in economics. Preferred Qualifications Possesses experience with at least one publication in a reputable economics journal or outlet. Teaching experience as a professor. Location & Other Expectations This position is based in Palo Alto, CA, or fully remote. The Palo Alto option is an in-office role requiring 5 days per week; remote positions require strong self-motivation. If you are based in the US, please note we are unable to hire in the states of Wyoming and Illinois at this time. We are unable to provide visa sponsorship. Team members are expected to work from 9:00am - 5:30pm PST for the first two weeks of training and 9:00am - 5:30pm in their own timezone thereafter. For those who will be working from a personal device, please note your computer must be a Chromebook, Mac with MacOS 11.0 or later, or Windows 10 or later. You must own and have reliable access to a smartphone. Compensation $45/hour - $100/hour The posted pay range is intended for U.S.-based candidates and depends on factors including relevant experience, skills, education, geographic location, and qualifications. For international candidates, our recruiting team can provide an estimated pay range for your location. Benefits: Hourly pay is just one part of our total rewards package at xAI. Specific benefits vary by country, depending on your country of residence you may have access to medical benefits. We do not offer benefits for part-time roles.xAI is an equal opportunity employer. California Consumer Privacy Act (CCPA) Notice

false

About the Role This role focuses on building the strategic unit economics understanding of OpenAI, guiding sustainable growth to make it the most impactful company of our generation and beyond.You will lead the development of foundational causal inference and data science models and frameworks to predict and quantify the drivers of customer lifetime value (LTV), translating deep data insights into strategic decisions and growth levers. The role requires both technical depth and executive-level communication.This position is based in our San Francisco HQ with a hybrid work model (three days in office per week). Relocation assistance is available.The VisionBuild causal inference and predictive analytics capabilities to measure and forecast LTV across customer segments (B2C and B2B), and quantify the incremental impact of different actions or product features on customer LTV.Design customer “happy paths” by identifying adoption journeys that maximize lifetime value while ensuring customers gain the most from our ecosystem.Analyze price elasticity to guide product packaging, monetization, and pricing strategies.In this role, you will:Partner with cross-functional teams (Finance, Product, Data Engineering, GTM, and other DS teams) to build causal inference and predictive models that drive business decisions.Develop and maintain LTV models across product lines and customer cohorts.Architect scalable frameworks and models that democratize economic insights for leadership and functional teams.Support strategic pricing and investment decisions with robust analytical and causal evidence.Lead cross-functional data science initiatives, ensuring analytical rigor, clarity, and timely delivery.You might thrive in this role if you:Executive communication — ability to distill complex analysis into clear, actionable recommendations for leadership.Technical breadth — comfort spanning ROI analysis, causal inference, statistical modeling, and ML predictive models; strong experience with Python and SQL.Strategic judgment — ability to connect analytical insights to business impact, delivering the “so what” that informs leadership decisions.Collaboration and ownership — thrive in a fast-paced, cross-functional environment and proactively take projects from concept to delivery.QualificationsMS or PhD in a quantitative field (Statistics, Economics, Applied Math, Operations Research, Computer Science, etc.).7+ years of experience in applied data science, causal inference, or quantitative strategy.Proven record of delivering high-impact insights to executive leadership.Experience building scalable analytical frameworks and models that inform business decision-making.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

false

About us PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software. We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations — empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive. Who We're Looking For As a Senior Data Scientist in Delivery, you are an experienced problem solver and technical leader who is passionate about building practical solutions that enable customers to make better engineering decisions. You are someone who can grasp advanced engineering concepts across multiple industries, lead technical initiatives, and excel at working directly with customers (and often side-by-side with them on-site) to embeds cutting edge AI models into tools that are useful and used. You've consistently tackled difficult problems that require strong foundations in data driven modelling and deep learning techniques, with extensive hands-on experience in probabilistic methods and predictive modelling. Your expertise in python, along with advanced proficiency in libraries like NumPy, SciPy, Pandas, TensorFlow and PyTorch, is essential, with proven ability to architect and deploy scalable, production-ready models and data pipelines. With 3-5 years of industry experience (post Masters of PhD) in a commercial, non-research environment, you're ready to not only execute but also lead and mentor others. You're truly excited about growing both your technical expertise and leadership skills, naturally taking ownership of complex data science work streams and guiding teams to success. You continuously improve the systems and solutions you work on to ensure they are practical, impactful and meet the evolving needs of our customers.   This Role In this senior role, you'll work closely with our Simulation Engineers, Machine Learning Engineers, and customers to understand and define the engineering and physics challenges we are solving, while providing technical leadership to your team. You'll build the foundations for successful, impactful solutions by: Leading pre-processing and analysis of complex data to prepare it for use in predictive modelling, establishing best practices and methodologies for your team. Architecting and developing innovative deep learning models in combination with state-of-the-art optimisation methods to predict and control the behaviour of physical systems. Taking full responsibility for the quality, accuracy and impact of your work and the work of your team. Designing, building, and testing data pipelines that are reliable, scalable, and robustlyeasily deployable in production environments. Leading cross-functional collaboration with simulation engineers to ensure seamless integration of data science models with simulations. Driving internal R&D and product development, helping to refine models and identify new areas of application. Mentoring junior team members and providing technical guidance to help them grow. Leading open communication and presentations with both technical teams and customers, helping onboard users and co-develop with customers. Representing PhysicsX as a technical authority when traveling to customer sites in North America, Europe, Asia, Oceania, an average of 2-3 weeks per quarter, where you'll collaborate closely with customers to build solutions on site. As a senior member of the team, you'll have significant influence on our technical direction and the opportunity to shape future solutions and products, while developing your skills as a technical leader. Please note, this role is based in London, UK, working 2-3 days per week in our office. Our delivery teams drive innovation to turn AI models into practical solutions - read our blog to learn more about how you’ll contribute to this exciting journey! What we offer  Equity options – share in our success and growth. 10% employer pension contribution – invest in your future. Free office lunches – great food to fuel your workdays. Flexible working – balance your work and life in a way that works for you. Hybrid setup – enjoy our new Shoreditch office while keeping remote flexibility. Enhanced parental leave – support for life’s biggest milestones. Private healthcare – comprehensive coverage Personal development – access learning and training to help you grow. Work from anywhere – extend your remote setup to enjoy the sun or reconnect with loved ones.   We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics.    We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with UK employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.   

true

PLEASE NOTE: This is a fully remote contract opportunity, with an estimated duration of 6 months with the opportunity to be extended. To be eligible, you must have authorization to work in the country you reside in.  About the Program The Human Frontier Collective (HFC) Fellowship brings together top researchers and domain experts to collaborate on high-impact work that are shaping the future of AI. As an HFC Fellow, you’ll apply your academic and professional expertise to help design, evaluate, and interpret advanced generative AI systems—while gaining exposure to cutting-edge research and working alongside an interdisciplinary network of leading thinkers. What You'll Do Collaborative Work: Get invited to engage in high-impact projects with our partnered AI labs and platforms. Develop and evaluate complex financial scenarios to test and enhance AI accuracy in valuation, forecasting, and analysis; collaborate in interactive sessions to assess model outputs for market relevance and compliance; provide detailed feedback to improve AI capabilities; and contribute to specialized projects in financial modeling, risk assessment, and equity research. Join the HFC Community: Beyond the work, you’ll become part of a supportive, interdisciplinary network of innovators and thought leaders committed to advancing frontier AI across domains. Contribute to Research Publications: Collaborate with Scale’s research team to co-author technical reports and research papers—boosting your academic visibility and professional recognition. Who Should Apply Education: PhD, Master, BBA in Finance, Economics, or related degrees. Certifications: CFA or CPA strongly preferred. Professional Background: 5+ years in FP&A, Investment Banking, Portfolio Management, Financial Consulting, or equivalent research experience. Skills: Strong proficiency in financial modeling, valuation methodologies, forecasting, asset pricing, DCF analysis, market analysis, and risk assessment.  Professional Mindset: Detail-oriented, innovative thinker with a passion for financial technology and a commitment to collaboration. Prior experience with AI is not required, but a plus. Why Join the HFC? Advance Finance AI Solutions: Apply your financial expertise to solve complex, real-world challenges where your judgment shapes advanced AI reasoning and decision-making. Professional Development: High-impact finance experts expand their influence through review projects, advisory roles, and research—while deepening their AI expertise, sharpening analytical and financial skills, and gaining hands-on experience with cutting-edge AI applications. Join a Top-Tier Network: Collaborate with a global network of academics and experts to advance responsible AI through impactful, flexible research and training. 80% of our members come from leading institutions. Flexible Schedule: Set your own schedule, with flexible 10–40 hour weeks that fit around your life and other commitments. Competitive Pay: $80–$120/hr., depending on the projects. Application Process Apply: We review applications on a rolling basis. Complete a Challenge: Selected candidates will undertake a brief task designed to reflect HFC work and evaluate their domain expertise. Interview: Candidates will meet with the HFC team to discuss their research experience, professional background, and alignment with our mission to advance human-centered AI. Join the Collective: Successful candidates will receive an invitation to join the Human Frontier Collective Fellowship. PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.  We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision.  PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

false

About Faculty At Faculty, we transform organisational performance through safe, impactful and human-centric AI. With more than a decade of experience, we provide over 350 global customers with software, bespoke AI consultancy, and Fellows from our award winning Fellowship programme. Our expert team brings together leaders from across government, academia and global tech giants to solve the biggest challenges in applied AI. Should you join us, you’ll have the chance to work with, and learn from, some of the brilliant minds who are bringing Frontier AI to the frontlines of the world.About the roleThis is an exciting opportunity to join Faculty as the most senior data scientist in the Retail and Consumer business unit.Our Retail and Consumer experts are dedicated to helping clients in an industry which is being transformed by new technologies and evolving consumer expectations. Leveraging over a decade of experience in Applied AI, we combine exceptional technical and delivery expertise to empower businesses to adapt and thrive.What you'll be doingProject Leadership:Guide the technical delivery of custom data science solutions for clients, from initial discovery to deployment in productionOwn the end-to-end data science approach, designing and implementing the appropriate techniques - from classic to AI agents using LLMs - that are designed, optimised and applied at scaleDesign robust and scalable software architecture for the solutions you build, ensuring best practices in engineering and MLOps are followed.Partner with our commercial team and clients to build strong relationships, acting as a trusted technical advisor.Articulate intricate technical concepts and strategic decisions clearly and effectively to diverse audiences, from client-side engineers to C-suite executives.Team Mentorship:Formally manage and mentor a number of data scientists, taking responsibility for their career progression and professional growth.Provide targeted technical support and learning opportunities for data scientists on your project teams.Contribute to sustaining our culture, creating an atmosphere of collaboration and setting a high standard for performance and technical excellence.Technical LeadershipEstablish a distinct and differentiated data science vision for professional and financial services, and communicate that vision through external thought leadership and in potential client presentations.Partner with our commercial team to ensure potential projects and programmes of work are appropriately resourced, balancing client delivery, colleague wellbeing, and commercial imperatives.Keep abreast of the latest technical and technology advancements, share these with others in the organisation, and identify how they can help drive Faculty forward.Who we're looking forYou have deep technical expertise in machine learning and a command of diverse methodologies, with a solid grasp of data science and statistical techniques, for example: supervised/unsupervised machine learning, model cross-validation, Bayesian inference, and time-series analysisAn excellent proficiency of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch)Demonstrable experience enabling impactful change with AI within a financial services institution. Coupling that with prior experience in consulting would be a bonus.You possess proven experience leading data science projects and making key decisions on technical direction and architecture.You are an exceptional communicator, capable of building rapport with clients and translating complex ideas into clear, actionable insights.You have a strategic mindset, with a grasp on key financial services sector trends that informs a compelling technical vision.You are passionate about developing people and have experience mentoring or managing other technical professionals.You are motivated to contribute to the wider data science community. We will actively support you in building your professional profile by speaking at major conferences, delivering courses, or contributing to open-source projects.What we can offer you: The Faculty team is diverse and distinctive, and we all come from different personal, professional and organisational backgrounds. We all have one thing in common: we are driven by a deep intellectual curiosity that powers us forward each day. Faculty is the professional challenge of a lifetime. You’ll be surrounded by an impressive group of brilliant minds working to achieve our collective goals. Our consultants, product developers, business development specialists, operations professionals and more all bring something unique to Faculty, and you’ll learn something new from everyone you meet.