Top Data Science Jobs in San Francisco Bay Area, CA

Lead GTM data science initiatives to build revenue forecasting, causal inference analyses, and AI-enabled solutions that improve sales, retention, and expansion. Partner with Product, Growth, and Commercial teams to operationalize insights, communicate findings to stakeholders, and mentor junior data scientists.

Lead payments-focused data science work: build foundational datasets, metrics, and scalable analytics; analyze customer and transaction behavior (including onchain data); conduct strategic analyses to identify product and revenue opportunities; build reporting, dashboards, and automation; and influence product and business strategy through data storytelling to senior stakeholders.

Lead end-to-end direct mail marketing campaigns: define targeting and suppression logic, execute and validate data pipelines, manage offshore execution, measure ROI and experiment results, partner with marketing and third parties to optimize audiences and campaign performance, and present insights to senior leadership.

As a Staff Data Scientist at Gusto, you will drive data-informed decision-making, lead projects, collaborate with teams, and mentor others in statistical analysis and experimentation.

Technical lead for Growth Analytics: partner with Growth/Marketing/Sales to identify opportunities, design experiments and statistical models, build scalable measurement frameworks, mentor junior data scientists, translate business questions into analytic solutions, and communicate insights to drive acquisition, activation, retention, and reactivation.

The Data Scientist will build predictive models, design data pipelines, conduct analyses, and deploy solutions in a collaborative environment.

Lead end-to-end data science for Cash App lending products: define measurement frameworks, run experiments, evaluate model and policy performance, detect bias/drift, build decision support, and mentor junior data scientists while partnering with product, engineering, and risk.

Build and productionize end-to-end fraud and financial risk models: data acquisition, feature engineering, labeling, training, experimentation, deployment, and monitoring. Research new fraud types, drive product development, support data quality and access, and present analyses to inform product, operations, sales, and marketing.

Lead product analytics efforts by designing and evaluating experiments, building dashboards, and producing statistical insights. Partner with product, design, and engineering to measure product success, identify optimization opportunities, and embed ML-driven personalization into the product.

As a Senior Data Scientist, the role involves leveraging data analysis, experimentation, and statistical methods to influence business decisions and enhance Gusto's product performance, while mentoring team members.

Lead measurement and decision systems for patient growth: own incrementality, design experiments, build LTV/retention/forecasting models, create trusted marketing metrics, partner with Engineering for measurement plumbing, diagnose performance shifts, influence channel allocation, and mentor growth analytics teams.

Lead product measurement strategy and complex evaluation for major product areas. Own experimentation standards, design causal and Bayesian analyses, build scalable measurement systems and dashboards, drive cross-team initiatives, mentor data scientists, and influence product decisions to improve mental healthcare outcomes.

As a Product Data Scientist, you will analyze user behavior, drive experimentation, build data tools, and collaborate across teams to influence product strategy and innovation at Whatnot.

Lead commercial data science for Headway's commercial business: own roadmap, run proactive strategic analyses for executive accounts, monitor key metrics, enable self-service analytics, mentor data scientists, and translate technical findings into actionable recommendations tied to measurable outcomes.

Lead product analytics to inform strategy and optimize user experience: translate business questions into analysis, build reliable analytics infrastructure, run A/B tests and ML/statistical analyses, track funnels and cohorts, support 0-to-1 product launches, and communicate actionable insights to cross-functional teams.

Build actuarial and health-economic models (total cost of care, PMPM, MLR) from claims to project multi-year cost and utilization impacts, quantify uncertainty, support commercial pricing, defend analyses to payer actuaries, partner on causal/expt design, and produce outputs usable for pricing/reserving.

Lead teams applying advanced data science and machine learning to large-scale claims, clinical, and member data to generate actionable insights that reduce cost of care and improve population health. Manage client relationships, mentor staff, ensure project delivery and quality, develop payer-focused analytics products, present findings to senior stakeholders, and promote continuous improvement and knowledge sharing.

The role involves analyzing fraud and risk data, defining KPIs, collaborating on anti-fraud strategies, and creating tools and dashboards for data accessibility at Whatnot.

Lead pricing modeling and experimentation to optimize margin, conversion, and retention. Build elasticity and willingness-to-pay models, design A/B and bandit experiments, develop pricing automation (DealBot) and monitoring for AI-driven rate recommendations, own ETL/analysis/visualization, and partner with Finance, Risk, Product, and GTM teams to operationalize pricing intelligence.

Lead end-to-end data science for lending products: define measurement frameworks, analyze experiments and cohorts, evaluate risk and model performance, use AI tools to accelerate analysis, build reusable tooling, and mentor junior scientists while partnering with product, engineering, and risk stakeholders.

Lead GTM-focused data science initiatives: build revenue forecasts, apply causal inference, develop AI-enabled sales and retention solutions, partner with Product/Growth/Commercial teams, and translate analyses into scalable, automated workflows and executive-ready recommendations.

Partner with Growth, Marketing, Sales, and Product to measure and optimize marketing and growth initiatives. Build dashboards and scalable measurement frameworks, design experiments, analyze ROI and trends, provide actionable recommendations, and communicate results to technical and non-technical stakeholders.

The Data Scientist will analyze data to provide insights, partner with teams for metrics, develop models, and create accessible visualizations to influence product and program strategies.

Partner with Digital Assets, Finance, Treasury, and Risk to design measurement frameworks, perform strategic analysis and modeling, build scalable SQL-driven automation and dashboards, analyze on-chain and finance data, create visualizations, and drive data-informed product decisions for USDC and related digital asset offerings.

Lead development, maintenance, and monitoring of credit risk models for lending portfolios. Use SQL and Python to build pipelines, perform EDA, forecast losses, automate dashboards, produce audit-ready documentation, support model governance/validation, and communicate insights to stakeholders.