Top Data Science Jobs

The Sr. Data Scientist in Aftersales Support develops predictive analytics and optimization solutions, models data processes, and collaborates on advanced reporting and dashboards.

Lead development of time-series and econometric models (ARIMA, VAR, state-space, WLS, panel data) and Bayesian probabilistic frameworks. Use causal inference and stochastic processes to produce actionable insights, work with large datasets on Databricks, communicate results to stakeholders, and mentor junior team members.

The Senior Data Scientist will lead data analytics projects, consult with clients, and develop data strategies and solutions, while managing a team and client relationships.

The Principal Data Scientist - Oncology will lead efforts in standardizing and connecting biomedical and clinical data through the development of scalable knowledge graph infrastructure and AI-Ready datasets.

The role involves leading advanced data science model development, collaborating with stakeholders, ensuring data quality, mentoring juniors, and staying updated on data science trends.

Lead a team of Data Scientists and Programmers to create data assets, insights, and reports impacting product decisions in gaming.

Lead a team of Data Scientists and Data Engineers to create data assets, reports, and insights, influencing Epic's product strategies.

Proactively explore RevenueCat data to identify customer problems and opportunities. Translate ambiguous product questions into analyses and production-grade predictive/descriptive models. Partner with Product, Engineering, and Analytics to shape roadmaps, define experimentation and benchmarking approaches, deploy and iterate on models powering customer-facing features, and communicate insights across technical and non-technical audiences.

Founding Data Scientist for RC Capital responsible for building underwriting, fraud detection, anomaly detection, and lead-qualification models; integrating risk signals into product flows; deploying and monitoring production models; analyzing cross-platform revenue data; and defining DS strategy to scale fintech products.

Transform analytical models into interactive GEOINT visualizations and analyst-facing interfaces, streamline production workflows, identify trends and insights, and operationalize geospatial data using Python, SQL, GIS tools, version control, and dashboarding frameworks to support mission-critical NGA/USSOCOM operations.

The Senior Data Scientist will oversee experiment design and analysis for user migration initiatives, collaborating with cross-functional teams and utilizing advanced statistical methods for decision-making.

Lead experimentation in user migration and marketing strategies, applying advanced statistical techniques and causal inference methods to drive business decisions.

Deliver end-to-end data science projects using machine learning and deep learning, collaborate with stakeholders, and support client engagement through analytical planning and solution design.

Manage and maintain data pipelines, improve data governance, and produce reproducible statistical analyses to inform transportation policy. Collaborate across teams, present findings to stakeholders, mentor colleagues, monitor data quality, and document data assets and methodologies.

Design, build, and maintain audit-focused data products, analytics, automation, and AI capabilities to improve audit coverage, efficiency, and risk insights. Partner with auditors and tech teams to deliver models, pipelines, dashboards, and workflow automation, support testing and deployment, and communicate findings to stakeholders.

Design, build, and productionize optimization, forecasting, and simulation models to support global supply chain decisions. Develop end-to-end pipelines (ingest, feature engineering, training, validation, deployment), perform scenario and sensitivity analysis, and collaborate cross-functionally to translate business needs into scalable analytic solutions and reusable components. Support model governance, monitoring, and adoption through storytelling and stakeholder engagement.

Own complex analyses and measurement frameworks for a product or business area. Design experiments and statistical/causal models, define and monitor KPIs, quantify impact, and translate findings into product and business recommendations. Partner cross-functionally, mentor junior analysts, and use tools like Python, SQL, Snowflake, dbt, Airflow, Spark, and AWS to scale analytics and ensure reproducibility and strong governance.

Lead data science work on the Matching team: translate product goals into analytics and ML problems, design and analyze A/B tests, mine data for product insights, and collaborate to develop and test production models that improve user matching.

Partner with product teams to define success metrics, design experiments, build dashboards and data models, validate data quality, analyze product performance, and translate insights into actionable recommendations to scale product analytics.

Lead end-to-end data science for customer-embedded, production solutions: acquire and prepare messy datasets, develop and evaluate models tied to business outcomes, run experiments, deploy operational models at scale, coach cross-disciplinary teams, and drive strategy, ethics, and privacy discussions.

Lead growth-focused data science to accelerate user adoption, engagement, and retention. Define measurement frameworks, build funnels and reusable datasets, design and analyze experiments using causal inference, develop behavioral segments, and partner cross-functionally to translate insights into product decisions and roadmap priorities.

Lead growth-focused data science work to accelerate adoption, engagement, and retention. Define measurement frameworks and core metrics, build funnels and reusable datasets, design and analyze experiments, apply causal inference, create behavioral segments, inform roadmaps, and partner cross-functionally to turn insights into product bets and measurable outcomes.

Lead end-to-end data science for aviation supply chain and operational data: integrate disparate sources, perform quality assessments, build predictive and statistical models (classification, regression, time series), document algorithms, and communicate results to stakeholders.

Lead a data science team to design, build, and deploy large-scale, real-time AI/ML solutions (forecasting, diagnostics, LLM chatbot, retention models, optimization) to optimize GPU cloud gaming performance and user experience.

The Senior Data Scientist will develop and maintain ML models and analytical frameworks to enhance customer experiences at CarMax, collaborating with Product and Operations teams to drive business-critical decisions and improve operational effectiveness.