Top Senior Data & Analytics Jobs in San Francisco Bay Area, CA

Lead data architecture strategies, drive innovation in data solutions, and oversee compliance with governance and security policies while collaborating with stakeholders to align technical solutions with business needs.

As a Senior Risk Investigator, you will identify, analyze, and mitigate risk, focusing on fraud detection and compliance in financial services. You'll conduct investigations, analyze data, collaborate with teams, prepare reports, and mentor junior staff.

As an Applied Research Engineer, you will drive the development of NLP systems, analyze data, collaborate with teams, and ensure efficient model integration.

Use large healthcare datasets to identify behavioral patterns, build product and client-facing analytics, partner with product and engineering to lead data projects from ingestion through analysis, and help shape data team strategy and recommendations.

Lead insights and data science strategies for the Payer Group at Headway, driving analytics to improve patient outcomes and collaborating with multiple stakeholders.

Lead transformation of Mastercard's enterprise data ecosystem. Define architecture of cloud-native data platforms, establish governance, and implement data engineering best practices.

Lead subscription analytics for SoFi Plus: define engagement/retention metrics, run deep-dive analyses and experiments, build scalable data pipelines and ML models, create executive dashboards, and influence product strategy to grow subscription value.

The Business Insights and Planning Manager drives growth through strategic analytics, annual sales planning, and revenue intelligence, while ensuring global alignment and effective communication with stakeholders.

As the Lead BI Engineer, you will build the analytical infrastructure for data-driven decision-making, design scalable data models and dashboards, implement BI tools, and ensure data quality. You'll partner with various teams to define KPIs and insights, setting the direction for future BI efforts and team growth.

Lead development of econometric, causal, and probabilistic forecasting models to guide Finance, Treasury, Sales, and Pricing. Design experiments and quasi-experimental analyses to identify business levers. Deploy production-quality Python models into AWS/Snowflake infrastructure and translate findings into strategic recommendations for executive and go-to-market teams.