Top Senior Analytics Jobs in San Francisco Bay Area, CA

As a Principal Data Analyst, you'll lead credit analytics efforts, develop forecasting models, and collaborate with multiple teams to enhance Upstart's credit platform.

The Staff Data Scientist will drive data-informed monetization strategies across subscriptions, advertising, and virtual currencies, collaborating with product and engineering teams and defining success metrics.

The Senior Manager, Risk Analytics will build and own Upstart's risk analytics program, managing Key Risk Indicators, data models, and reporting infrastructure for enterprise-wide risk monitoring and compliance. They will collaborate with risk owners and conduct data aggregation and reporting, supporting risk assessments and regulatory requirements.

The role involves analyzing fraud methodologies, executing data analysis, and influencing change through insights. It includes managing compromised credential risks and supporting data integrity.

Partner with cross-functional teams to analyze large healthcare datasets, build models and dashboards, and surface insights to reduce medical waste. Scope, run, and present analyses, monitor performance metrics, and support initiatives to improve financial and utilization outcomes.

The Senior Data Scientist will lead revenue-driving initiatives, optimize strategies, enhance data analysis techniques, and improve data pipelines for maximum revenue impact.

The Senior Data Scientist will design and deploy time-series forecasting models, collaborate with stakeholders, and operationalize models in cloud environments, focusing on demand planning across various industries.

Lead Quantitative Analysts in risk management data analysis, model creation, testing, and validation for business and regulatory compliance. Mentor junior analysts and present results to management.

The Staff Data Scientist will work with product teams to analyze data, identify improvement opportunities, design experiments, and create reporting dashboards to enhance contract management workflows.

The Manager leads the Predictive Analytics and Data Science team, develops predictive models, and collaborates with cross-functional teams to drive data-driven solutions in healthcare.

Lead digital measurement and analytics for ecommerce: build measurement frameworks, run attribution and predictive models, drive A/B testing and personalization, produce executive dashboards and actionable insights, partner cross-functionally to improve conversion, retention, and LTV.

The role involves owning data science pipelines, delivering client-facing features, driving cross-functional collaboration, and leveraging AI tools to enhance workflows, ultimately transforming retail data into actionable insights.

Lead analytics strategy for channel marketing, build attribution and incrementality frameworks, run experimentation and forecasting, surface optimization insights, and grow a high-performing analytics team to improve ROI and guide investment decisions.

The Fraud Risk Analytics Manager will lead fraud risk strategy optimization and provide analytical insights to reduce fraud risk and enhance customer outcomes. They will partner with teams to ensure transparency and governance in fraud strategies, using advanced data analysis techniques to drive decision making.

The Senior Analyst will support fundraising data-driven decisions, develop KPIs, analyze campaigns, and collaborate on revenue forecasting through data modeling, analysis, and reporting.

The Risk Analytics Senior Manager analyzes business problems, tests hypotheses with data, and communicates insights to senior management, focusing on credit risk policies.

Manage a team of ~7 data scientists to deliver experimental design, product analytics, and actionable insights. Partner with product, engineering, and research to build measurement, data products, and reporting; ensure data accuracy, timely delivery, and best practices.

Lead a team of ~7 data scientists to deliver timely, accurate product analytics and experimentation insights. Manage people, partner with product and engineering, improve measurement and data products, and ensure rigorous large-scale analysis to inform product decisions.

Lead a Product Analytics data science team to deliver timely, accurate insights for product decisions. Manage ~7 data scientists, mentor teammates, partner with product and engineering, develop experimentation and measurement best practices, and build accessible data products and reports.

Lead a team of ~7 data scientists to deliver timely, accurate product analytics and experiments; support product teams, build accessible data products, mentor staff, and improve measurement and reporting practices.

Lead a team of ~7 data scientists to deliver timely, accurate product analytics: guide experimentation, partner with product and engineering, build accessible data products, mentor staff, and improve measurement and reporting practices to inform product decisions.

Lead the Retention Analytics team by providing insights into subscriber journeys, data analysis for retention strategies, and managing a team of analysts.