Top Senior Data Science Jobs in San Francisco Bay Area, CA

Lead data-driven strategy for Pinterest Ads by translating business needs into analytical solutions, ensuring data quality, connecting product and financial performance, advising cross-functional leaders, and elevating data science practices across the organization.

The Data Scientist will analyze data to enhance business performance, engage customers, and optimize product strategies through experimentation and metrics establishment.

Lead SMB Ads analytics end-to-end: define growth KPIs, diagnose funnel friction, build propensity/LTV models, design attribution and A/B experiments, automate dashboards, and forecast advertiser/revenue growth to inform product and marketing decisions.

Lead measurement and insights for ads demand: define metrics and benchmarks, analyze advertiser performance, build early-warning signals, design experiments, translate findings into sales and product actions, forecast opportunities, and close feedback loops to improve advertiser outcomes.

Lead the fraud data science function: define ML strategy, build and deploy real-time fraud detection models, investigate fraud patterns (including lending fraud), run experiments, collaborate with stakeholders, and maintain monitoring and dashboards to minimize fraud losses.

Lead Fraud Data Scientist to define ML strategy, build and productionize fraud detection models (supervised and unsupervised), investigate emerging fraud patterns, run experiments, collaborate with Product/Engineering/Risk, and maintain dashboards tracking fraud KPIs.

Lead the fraud data science function: define ML strategy, build and productionize fraud and lending-fraud models, run advanced analyses (clustering, network analysis), design A/B tests, integrate ML with rules engines, monitor models in cloud, and communicate results to stakeholders.

Build, test, deploy, and monitor ML models for credit risk, fraud detection, and transaction timing. Create training datasets, run experiments and A/B tests, analyze customer trends, and collaborate with Engineering, Product, and Business teams to deliver end-to-end data science solutions.

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.

Lead data science across autonomy, safety, and product by analyzing machine telemetry and operational data, defining metrics, designing experiments, and partnering with ML platform and engineering to deliver insights that improve system performance and safety.

As the first Data Scientist, you will analyze user data and AI outputs to enhance content creation, define metrics, conduct A/B testing, and collaborate closely with cross-functional teams to improve product features.

Build and operate GTM intelligence decision products: define features, methods, pipelines, monitoring, and evaluations; partner with GTM stakeholders to prioritize accounts, surface risks and opportunities, ship production Python/SQL workflows, and iterate using field feedback and outcomes.

Partner with product, engineering, design, ops, and clinical teams to define metrics and experiments. Design and analyze A/B tests and quasi-experiments, apply causal inference when needed, perform funnel/cohort analyses, build and validate predictive models, and operationalize insights with monitoring and launch criteria. Produce clear, decision-ready analyses and raise organizational standards for metrics and experimentation.

As a Data Scientist at Anthropic, you'll support data-driven decisions across the customer lifecycle by defining metrics, analyzing data, and developing statistical models. You'll collaborate with various teams to influence strategies and improve analytics infrastructure.

Founding Data Scientist for Procure-to-Pay working cross-functionally to build models, metrics, simple data pipelines, dashboards, and reports. Analyze complex datasets, produce actionable insights through data storytelling, and partner with leadership to turn business problems into data-driven solutions that impact operations and growth.

The Data Scientist role involves developing measurement models, writing production-quality code in Python, and collaborating with teams to optimize data pipelines and ML workflows.

Lead development of automated, auditable revenue data pipelines and anomaly detection to improve reconciliation and data integrity. Build reusable financial data assets, dashboards, and reports; collaborate with finance and cross-functional teams to support month/quarter-end close and audit readiness.

Lead data-driven strategy by partnering with senior executives to deliver rigorous analytical solutions. Design and implement sophisticated analyses on large-scale data, build trusted cross-functional relationships, mentor data scientists, and influence long-term product and business decisions.

As a Staff Data Scientist, you'll develop and deploy machine learning models to enhance renter experiences and optimize property partnerships, collaborating across teams to translate data insights into actionable strategies.

Lead the experimentation science roadmap for Waymo's marketplace platform. Design advanced causal inference and experimental methods for spatial-temporal and network effects, set best practices, partner with engineering to productionize pipelines, and translate results into clear product strategy for stakeholders.

As a Senior Data Scientist, you'll develop fraud detection models, perform detailed analyses, and work closely with teams to drive product innovation and business outcomes.

Lead the fraud data science function: define ML strategy, build and productionize fraud detection models, investigate fraud patterns, run experiments, collaborate with Product/Engineering/Risk, and deliver dashboards and monitoring to minimize fraud losses while preserving customer experience.

Lead the fraud data science effort: define ML strategy, build and productionize real-time fraud detection models, investigate fraud patterns with unsupervised and graph techniques, run experiments, collaborate with product/engineering/risk, and maintain dashboards to monitor model performance and fraud KPIs.

The Senior Data Scientist will analyze data to drive product strategy, optimize performance, and support product launches, collaborating with cross-functional teams.

Build and maintain data science models and quantitative measurement frameworks to guide infrastructure decisions (chargers, parking, depots). Analyze infra efficiency and identify improvements. Collaborate cross-functionally with Supply Operations, Product, and Engineering to incorporate business context into model-driven decisions supporting expansion to new territories and cities.