AI Applied Data Scientist Jobs

Discover the latest remote and onsite AI Applied Data Scientist roles across top active AI companies. Updated hourly.

Check out 13 new AI Applied Data Scientist opportunities posted on The Homebase

Data Scientist, Integrity Measurement

New
Top rated
OpenAI
Full-time
Full-time
Posted

The data scientist will own measurement and quantitative analysis for several severe, actor- and network-based usage harm verticals, including estimating prevalence of on-platform and sometimes off-platform harms. They will develop and implement AI-first methods for prevalence measurement and other safety metrics using non-standard datasets if necessary, build metrics used for goaling or A/B tests, and own dashboards and metrics reporting for harm verticals. The role involves conducting analyses and generating insights to improve review, detection, or enforcement, optimizing LLM prompts for measurement purposes, collaborating with other safety teams to address safety concerns and create relevant policies, providing metrics for leadership and external reporting, and developing automation to scale their work using agentic products.

Undisclosed

()

London, United Kingdom
Maybe global
Onsite

Data Scientist, Integrity Measurement

New
Top rated
OpenAI
Full-time
Full-time
Posted

The data scientist will own measurement and quantitative analysis for a group of severe, actor- and network-based usage harm verticals. They will develop and implement AI-first methods for prevalence measurement and other productionised safety metrics, build metrics suitable for goaling or A/B tests when prevalence or other top line metrics are not appropriate, and own dashboards and metrics reporting for harm verticals. They will conduct analyses and generate insights to inform improvements to review, detection, or enforcement, and influence safety roadmaps. The role involves optimizing LLM prompts for measurement purposes, collaborating with other safety teams to understand key safety concerns and create relevant policies, providing metrics for leadership and external reporting, and developing automation to scale their work using agentic products. The position may involve resolving urgent escalations outside normal work hours and may require working with sensitive content including sexual, violent, or otherwise disturbing material.

$293,000 – $385,000
Undisclosed
YEAR

(USD)

San Francisco, United States
Maybe global
Onsite

Senior Data Scientist

New
Top rated
Faculty
Full-time
Full-time
Posted

As a Senior Data Scientist at Faculty, you will be responsible for designing and building AI-powered computational twins tailored for each unique Frontier deployment. You will lead data science efforts within cross-functional teams, collaborating with engineers, designers, and commercial leads to ensure project success. Your role involves deeply understanding core customer challenges to deliver significant real-world value, conducting rigorous exploratory data analysis, model building, validation, and performance monitoring. Additionally, you will support client relationships by partnering with the commercial team to shape strategic project direction and mentor other data scientists through task leadership and potential line management.

Undisclosed

()

London, United Kingdom
Maybe global
Hybrid

Data Scientist, Support

New
Top rated
OpenAI
Full-time
Full-time
Posted

The Support Data Scientist will explore large support and product datasets to uncover trends, volume drivers, and user-experience pain points, distilling findings into clear, actionable narratives. They will build, enhance, and maintain self-serve dashboards and reporting tools for non-technical teams. The role involves establishing a unified metrics taxonomy for service-health and performance, and building automated data-sharing pipelines and scorecards with BPO partners. They will leverage LLMs to build bespoke classifiers to automatically label and segment inbound volumes, partner with Data Engineering to ensure reliable pipelines and data quality, and document sources of truth. The role also includes conducting deep-dive analyses and delivering strategic recommendations to leadership, prototyping rapidly with tools like ChatGPT and Jupyter notebooks, and collaborating with Data Science on predictive models and experimentation to translate results into operational recommendations.

$230,000 – $255,000
Undisclosed
YEAR

(USD)

San Francisco, United States
Maybe global
Hybrid

Data Science Intern, Summer 2026

New
Top rated
Crusoe
Intern
Full-time
Posted

As a Data Science Intern at Crusoe, you will design and implement a robust data pipeline to ingest and preprocess large volumes of syslog data from diverse network devices, develop methods to group and normalize unstructured log messages, build statistical or machine learning-based baseline models to define normal behavior patterns across the network environment, and implement anomaly detection mechanisms for multiple time scales. You will create functional alerting or visualization mechanisms to communicate critical findings, evaluate and optimize signal quality to reduce false positives, document assumptions and system limitations, and collaborate with network and systems engineers to refine the relevance of detected anomalies.

$1,690 – $1,690
Undisclosed
YEAR

(USD)

San Francisco, United States
Maybe global
Onsite

Data Science Manager, Integrity

New
Top rated
OpenAI
Full-time
Full-time
Posted

Lead and scale a high-impact Integrity Data Science team by hiring, coaching, and developing data science individual contributors and potentially future managers while setting a strong technical and cultural bar. Drive strategy across multiple Integrity domains including policy enforcement, bot detection, fraud prevention, intellectual property theft, risk measurement, and abuse prevention, balancing near-term response with durable systems. Build and institutionalize analytical rigor through clear metric frameworks, experimentation standards, monitoring and alerting systems, and repeatable evaluation approaches for Integrity interventions. Partner closely with Product and Engineering to shape roadmaps, prioritize projects, and translate ambiguous risk signals into practical product and platform decisions. Evolve team structure and operating model as the organization scales by defining ownership boundaries, improving processes, and creating leverage through better tooling and AI-assisted workflows. Enable cross-organization outcomes by supporting partners outside the Integrity team where integrity risks intersect with product and business goals. Communicate clearly with senior leadership to synthesize complex tradeoffs, surface risks, and drive alignment on priorities and success metrics. Push the team toward an AI-leveraged operating mode using modern tooling and model capabilities to accelerate detection, triage, analysis, and iteration.

$255,000 – $490,000
Undisclosed
YEAR

(USD)

San Francisco, United States
Maybe global
Onsite

Data Scientist - Network Value

New
Top rated
Plaid
Full-time
Full-time
Posted

Perform ad-hoc and strategic analyses to uncover opportunities for improved business outcomes and translate complex questions into actionable analytics projects. Design and maintain scalable data models and dashboards that increase visibility into core systems and drive operational excellence. Build and iterate on machine learning prototypes to power insight-driven products and unlock new sources of customer and business value. Define and track OKRs that quantify progress toward key business goals, ensuring alignment and accountability across teams. Design and analyze experiments to guide product decisions and optimize feature launches. Champion a data-first culture by promoting analytical rigor and evidence-based decision-making across the organization.

$162,000 – $222,000
Undisclosed
YEAR

(USD)

San Francisco, United States
Maybe global
Onsite

Staff Data Scientist | Content Gen

New
Top rated
Machinify
Full-time
Full-time
Posted

The Staff Data Scientist role involves leading the build and deployment of classical ML and GenAI systems to generate and validate billing error, audit, and fraud concepts in healthcare payments. The responsibilities include building and shipping ML and GenAI pipelines to identify and rank candidate billing error and fraud concepts across large-scale healthcare claims data, advancing research in anomaly detection, information retrieval, and weak supervision into production systems, designing human-in-the-loop workflows to accelerate concept generation and validation with subject matter experts (SMEs), owning end-to-end delivery from problem framing to deployment and monitoring with a focus on reliability and customer outcomes, partnering cross-functionally with product, data engineering, operations, SMEs, and business leaders to prioritize and execute work with financial impact, and helping to scale the team and platform as the company grows towards resale and IPO readiness.

Undisclosed

()

Palo Alto, United States
Maybe global
Remote

Marketing Intern - Seoul

New
Top rated
Dataiku
Intern
Full-time
Posted

Help users discover and master the Dataiku platform through user training, office hours, demos, and ongoing consultative support. Analyse and investigate various kinds of data and machine learning applications across industries and use cases. Provide strategic input to the customer and account teams that help our customers achieve success. Scope and co-develop production-level data science projects with our customers. Mentor and help educate data scientists and other customer team members to aid in career development and growth.

Undisclosed

()

Seoul, South Korea
Maybe global
Hybrid

Marketing Intern - Tokyo

New
Top rated
Dataiku
Intern
Full-time
Posted

Help users discover and master the Dataiku platform through user training, office hours, demos, and ongoing consultative support. Analyse and investigate various kinds of data and machine learning applications across industries and use cases. Provide strategic input to the customer and account teams that help our customers achieve success. Scope and co-develop production-level data science projects with our customers. Mentor and help educate data scientists and other customer team members to aid in career development and growth.

Undisclosed

()

Tokyo, Japan
Maybe global
Hybrid

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Frequently Asked Questions

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[{"question":"What does a AI Applied Data Scientist do?","answer":"AI Applied Data Scientists develop statistical models and machine learning algorithms to solve business problems. They analyze complex datasets to extract insights, identify patterns, and drive decision-making. Their responsibilities include preprocessing data, designing experiments, conducting A/B tests, and measuring solution effectiveness. They collaborate with data engineers and stakeholders to build data pipelines, communicate findings through visualizations, and deploy scalable machine learning models while monitoring their performance."},{"question":"What skills are required for AI Applied Data Scientist?","answer":"The role requires proficiency in programming languages like Python, R, and SQL, plus experience with machine learning frameworks for building predictive models. Strong statistical analysis abilities are essential for feature selection and data interpretation. Familiarity with data visualization tools helps in creating effective dashboards. Experience with A/B testing, telemetry data analysis, and LLMs/prompt engineering is increasingly valuable. Collaboration skills are necessary for working across teams to implement solutions."},{"question":"What qualifications are needed for AI Applied Data Scientist role?","answer":"Employers typically seek candidates with at least 1-5 years of experience in applied data science or quantitative roles. A background in algorithms, A/B testing, and product analytics is important. Proficiency in SQL and Python for experiments and metrics tracking is essential. Experience with data pipelines, metrics creation, and trend analysis strengthens applications. Many positions prefer candidates with knowledge of NLP, large language models, or generative AI technologies."},{"question":"What is the salary range for AI Applied Data Scientist job?","answer":"The research provided doesn't include specific salary information for AI Applied Data Scientist positions. Compensation typically varies based on factors including geographic location, industry, company size, years of experience, and specific technical expertise. Salaries often reflect the specialized nature of combining AI knowledge with applied data science skills, which commands higher compensation than general data analysis roles in most markets."},{"question":"How long does it take to get hired as a AI Applied Data Scientist?","answer":"The hiring timeline for AI Applied Data Scientist positions isn't specified in the research. The process typically involves multiple interview rounds testing technical skills, problem-solving abilities, and domain knowledge. Candidates with experience in machine learning algorithms, statistical modeling, and programming languages like Python may progress more quickly. The hiring process can extend longer for roles requiring specialized AI knowledge or when companies conduct rigorous technical assessments."},{"question":"Are AI Applied Data Scientist job in demand?","answer":"While the research doesn't provide specific demand numbers, industry signals suggest AI Applied Data Scientist roles are growing in importance as businesses increasingly rely on predictive analytics and machine learning solutions. The specialized intersection of AI knowledge with applied data science skills makes these professionals valuable across industries. Companies seek candidates who can translate complex data into actionable business insights while building and implementing machine learning models."}]