Senior Data Scientist
Designing and building agents in high-consequence environments where outputs need to be validated to a high standard, performing exploratory data analysis, model building, validation, and performance monitoring, leading data science efforts within cross-functional delivery teams by partnering with engineers, designers, and product leads for successful outcomes, understanding deeply core customer problems to ensure technical solutions drive real value, and translating real-world problems into technical strategies and measuring model impact with scientific rigor.
Data Scientist
Collect, process, and analyze large datasets from multiple sources Build and deploy machine learning models to solve business problems Design and implement A/B tests and statistical analyses Collaborate with cross-functional teams (product, engineering, marketing) to define analytics requirements Communicate complex data insights in a clear and actionable manner to stakeholders Develop dashboards and visualizations to monitor key metrics Stay current with the latest trends and technologies in data science and AI
Senior Data Scientist, Marketing
The Senior Marketing Data Scientist will partner closely with Harvey’s Marketing organization to build the marketing data science function from the ground up. Responsibilities include embedding deeply with the Marketing organization as a trusted partner to identify opportunities to improve performance and drive growth, defining, tracking, and evolving core metrics across marketing and business functions, and building scalable dashboards and reporting frameworks that enable data-driven decision-making. The role involves designing, implementing, and evaluating models such as multi-touch attribution, marketing mix modeling, and incrementality for comprehensive Marketing Channel and Campaign performance and contribution. The Senior Data Scientist will apply statistical and machine learning techniques to model user behavior, forecast trends, and identify opportunities for growth and optimization. They will translate complex analyses into compelling stories with clear recommendations for cross-functional partners and executives, partner with Marketing, RevOps, and GTM Systems to co-develop data infrastructure ensuring robust pipelines, reliable data sources, and scalable systems to power analytics and modeling. The role also includes leading cross-functional analytics initiatives to synthesize competitive dynamics, customer feedback, and market trends into actionable business opportunities and championing a data-informed culture by establishing best practices, mentoring peers, and shaping the strategic role of data science at Harvey.
Data Scientist | ML
Master understanding of various claims payment policies and healthcare concepts; build and improve models by thoughtfully curating data and creating features; precisely measure and improve model performance against real-world outcomes and make operational recommendations to optimize model results; interpret and refine large-scale data created by complex business workflows; advance the team’s capabilities by improving pipelines, infrastructure, and tools.
Signal Engineer
The Signal Engineer is responsible for designing, sourcing, shaping, and evaluating input signal at scale to enable AI models to learn faster, learn better, and generalize more effectively. This includes working deeply with raw and synthetic data, designing new datasets and signal mixtures, iterating on input distributions and formats, understanding how small changes in signal affect training behavior, thinking across stages of training rather than in isolation, and treating data as a dynamic, evolving system rather than a static asset. The role involves immersion, experimentation, and developing intuition through long feedback loops, using computational environments and technical tooling, working directly with data through scripts, notebooks, and experimental pipelines, modifying existing systems, and building small utilities to explore questions.
Principal Data Scientist
Take part in building a platform used by Data Scientists and Simulation Engineers to build, train and deploy Deep Physics Models. Work on a focused, stream-aligned and cross-functional team (back-end, front-end, design) that is empowered to make its implementation decisions towards meeting its objectives. Gather and leverage domain knowledge and experience from the Data Scientists and Simulation Engineers using your product.
Quantum Computing Researcher
The role involves designing, sourcing, shaping, and evaluating input signal at scale to improve AI model learning speed, quality, and generalization across the entire training lifecycle. Responsibilities include working deeply with raw and synthetic data, designing new datasets and signal mixtures, iterating on input distributions and formats, understanding small changes in signal and their effects on training behavior, and considering the entire training stages as a dynamic and evolving system rather than as static assets. It also requires immersion, experimentation, and developing intuition through long feedback loops.
Senior Data Scientist
As a Senior Data Scientist at LMArena, you will explore and analyze large, complex datasets to uncover patterns, biases, and causal relationships in model behavior and system performance. You will formulate hypotheses about data quality, evaluation outcomes, and model performance, then design experiments to validate or refute them. You will build reproducible analysis pipelines using Python, Pandas, NumPy, and Spark to process and interrogate large-scale data. You will partner with ML researchers and engineers to design metrics and analyses that evaluate how models perform across domains, prompts, and tasks. Additionally, you will develop causal reasoning frameworks and statistical methods to explain model behavior beyond performance metrics. You will communicate insights clearly to both technical and non-technical partners, informing research direction and infrastructure improvements.
Senior Data Scientist
The Senior Data Scientist will own Fyxer AI’s data science capabilities, setting the roadmap for key business areas like marketing and retention, implementing scalable solutions, and ensuring stakeholders use data to make confident commercial decisions. Responsibilities include building and refining predictive models on multi-channel customer and usage data to drive product and marketing decisions, collaborating with engineering, marketing, sales, and product teams to define KPIs, experiment with new algorithms, and surface actionable insights that drive impact. They will maintain data infrastructure including BigQuery, dbt, and Fivetran, ensure data quality for reporting and self-service analytics, and develop a culture of data-driven decision making by proactively suggesting improvements to tools, processes, and architecture.
Data Scientist - Manufacturing Data (KR)
Design and implement customized AI solutions for manufacturing; analyze manufacturing data to uncover opportunities and develop AI models; collaborate with customers to understand their requirements and deliver clear, data-driven solutions; work closely with internal teams to ensure solutions are feasible, scalable, and aligned with product strategy; present findings to both technical and non-technical stakeholders.
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