Top Senior Analytics Jobs in San Francisco Bay Area, CA

Analyze and optimize drug pricing using data-driven models, dashboards, reports, and strategic frameworks. Partner with Sales, Operations, Marketing, Finance, Product, pharmacy partners, and data teams to identify opportunities, define success metrics, improve reporting, and balance pharmacy economics with patient affordability. Serve as a trusted analytical advisor and support backend data development and query optimization.

Leads pricing and monetization analytics, measuring initiative impact and identifying growth opportunities. Defines performance metrics, builds dashboards and automated reporting, and creates frameworks for Corporate Strategy priorities. Partners with pricing, product, sales, deal desk, and field teams to provide actionable insights and operational enablement. Uses statistical analysis, AI tools, and data-driven guidance to improve decision-making and scale best practices.

Develop data models, analyses, dashboards, and automated reporting for a collectibles marketplace. Partner with engineering, product, and data platform teams to define business metrics, identify customer experience and growth opportunities, inform strategy, and lead initiatives that improve business performance.

Own product analytics for Heartflow’s platform by measuring adoption, retention, utilization, and feature impact. Design experiments and quasi-experimental analyses, establish product metrics and event taxonomies, build dashboards, and partner with Engineering on instrumentation. Translate quantitative and qualitative customer insights into product and commercial recommendations. Champion AI-enabled analytics, ensure data quality and compliance in a regulated medical-device environment, present findings to leadership, and mentor analysts.

Leads marketing and enrollment analytics across acquisition and conversion funnels. Analyzes channel performance, ROI, attribution, forecasting, experimentation, and marketing mix modeling; develops recommendations for budget allocation and performance improvement. Uses Power BI, SQL, Python or R, and institutional and marketing datasets to build models, automate monitoring, identify anomalies, and support cross-functional decisions. Owns marketing measurement standards, data quality, tracking, and analytical roadmap while partnering with Marketing, Enrollment, Field, and Institutional Analytics teams.

Analyzes business and operational needs, gathers requirements, evaluates data and systems, and recommends technology solutions. Develops advanced SQL queries, reports, system models, and process improvements. Responsibilities include troubleshooting, data architecture integration, software and hardware solution design, database analysis, automation using scheduling or RPA tools, and project leadership. Senior levels guide other analysts and assess technology’s business impact.

Leads fraud analytics to identify fraud methodologies, root causes, compromise points, volumes, and financial or operational impacts. Develops advanced analyses and actionable remediation recommendations for internal teams and participating financial institutions. Manages compromised credential processes, including identifying exposed credentials, social tokens, and payment information, assessing risk, and applying appropriate treatments. Requires experience in analytics coding, digital banking or payments, fraud risk management, and communicating insights to influence organizational change.

Own Bay FC’s fan analytics narrative and translate business, market, and consumer data into actionable commercial recommendations. Analyze revenue performance, growth opportunities, brand health, audience segments, fan lifecycle behavior, and campaign effectiveness. Partner with Marketing, Ticketing, Merchandise, and senior leadership on analytical projects, business reviews, testing frameworks, and executive-ready insights. Build unified fan profiles, guide audience targeting, and influence organizational strategy through clear data storytelling.

Leads quantitative data analytics and insights for investment risk forecasting, portfolio construction, performance measurement, and reporting. Designs Python- and R-based analytical tools, production data platforms, quality frameworks, and quantitative models. Supports portfolio managers and analysts through risk analysis, statistical modeling, data integrity controls, reporting automation, and infrastructure improvements. Works with multi-asset security data, factor models, derivatives, valuation, VaR, stress testing, and performance attribution while providing technical guidance and solutions to business partners and senior leadership.

Leads enterprise advanced analytics and modeling to identify drivers of business performance across brands, markets, customers, accounts, and geographies. Translates findings into prioritized actions, playbooks, launch strategies, and scenario-based recommendations. Oversees rigorous, scalable analytical approaches, partners with senior stakeholders, and develops analytics talent across the organization.

Owns end-to-end customer analytics workstreams, including KPI frameworks, multi-source dashboards, reporting, data governance, quality assurance, and insight delivery for government digital communications programs. Presents recommendations to stakeholders, mentors junior analysts, leads Agile ceremonies, documents analytics practices, resolves data issues, and evaluates AI-assisted analytics tools.

Analyze startup user and product data, identify trends and drivers, and turn findings into strategic recommendations. The role owns key metrics and dashboards, leads analytical deep dives, sizes opportunities, evaluates product tradeoffs, supports roadmap prioritization, and develops external-facing insights about startups in partnership with marketing and communications.

Owns analytics and optimization strategy for advertising revenue across Zynga’s mobile game portfolio. Responsibilities include monitoring performance, diagnosing trends, designing A/B tests, identifying monetization opportunities, partnering with product, analytics, and data science teams, supporting AI and ML models, leading cross-functional initiatives, and mentoring analysts.

Leads marketing and loyalty analytics strategy, measurement frameworks, forecasting, campaign reporting, experimentation, and lifecycle analysis. Partners with Marketing and Finance to connect performance metrics to business goals, automate reporting, and generate actionable insights. Builds churn, retention, segmentation, and LTV models while evaluating paid acquisition and customer growth opportunities using SQL, Python, BI tools, marketing platforms, and modern AI-enabled workflows.

Owns fraud performance analytics for depository products, including monitoring losses, approval rates, false positives, customer friction, and risk metrics. Builds data models, transformation pipelines, dashboards, scorecards, and monitoring frameworks. Conducts fraud deep dives and develops optimized rules, policies, thresholds, models, and decision strategies. Partners with Product, Engineering, Machine Learning, Data Engineering, Fraud Operations, and Risk teams to improve fraud detection and support product launches.

Leads advanced analytics across the organization, owning MAU forecasting and growth models, experimentation standards, and causal inference methods. Establishes analytical best practices, reviews high-stakes analyses, partners with data and product teams, and scales recurring work through AI tooling. Mentors data professionals and translates complex statistical findings into actionable leadership recommendations.

Leads analytics strategy and technical delivery for clients, specializing in Adobe Analytics and Customer Journey Analytics. Conducts measurement workshops, defines KPI and implementation strategies, oversees tagging and data quality, guides experimentation, and reviews dashboards and insights. Advises senior stakeholders, manages and mentors consultants, supports proposals and account growth, and contributes to Adobe Experience Platform initiatives involving Target, RT-CDP, and AJO.

Manage and grow Ashby’s data analytics team while remaining hands-on with analytical work. The role includes hiring and coaching analysts, improving data practices, prioritizing requests, developing specialization, maintaining analytical quality, and guiding responsible AI adoption. The manager will work across raw and modeled data, dbt models, metric definitions, dashboards, and internal data products, partnering closely with business teams in a remote, high-growth B2B SaaS environment.

Co-lead a 15+ person analytics team, define key performance indicators, build dashboards and reports, identify voter behavior insights, support product feature development through usage data, provide election activity reporting, and interview new volunteers. This remote volunteer executive role requires at least two hours weekly, five or more years of analytics experience, and preferably three or more years leading teams.

Analyze marketing and customer data to measure campaign impact, uncover customer insights, and improve marketing ROI. Build Tableau dashboards, write and optimize SQL queries, conduct segmentation and lifecycle analysis, validate data quality, and provide actionable recommendations. Partner with marketing, product, and analytics stakeholders to translate business needs into analytical solutions and support strategy across channels, including spend allocation, targeting, attribution, and campaign effectiveness.

Lead analytics support for Fetch’s Food and Beverage vertical, serving as the primary analytics partner for Sales and client stakeholders. Own sub-vertical partnerships, manage analytic capacity, answer senior-level client questions, and guide campaign strategy. Use SQL to manipulate data, develop actionable insights, support QBR storytelling, and communicate recommendations to technical and non-technical audiences. Represent analytics cross-functionally and automate insights using AI-enabled tools.

Manage and develop a team of 4–6 analysts delivering customer reporting and analytics. Lead complex analyses, establish standards for rigor and reproducibility, oversee project delivery, present findings to stakeholders, and partner with Product and Engineering on measurement products and AI-enabled analytics tools. The role requires deep advertising measurement expertise, client-facing communication, dashboard development, and hands-on proficiency in SQL, Python, Excel, statistical methods, and analytics platforms.

Leads marketing and loyalty analytics strategy, measurement frameworks, forecasting, experimentation, campaign reporting, retention analysis, churn modeling, and segmentation. Partners with Marketing and Finance to establish performance goals and translate complex data into actionable recommendations. Automates reporting using analytics platforms, marketing automation tools, experimentation methods, and AI-enabled workflows while identifying opportunities to grow and retain high-value consumers.

Lead insurance risk analytics engagements for property and casualty carriers. Responsibilities include product demonstrations, regulatory filing guidance, pilot and proof-of-concept design, loss ratio and model validation analysis, client project management, discovery sessions, and translating insights for actuarial, underwriting, and executive audiences. The role also develops AI-assisted workflows and provides customer feedback to product teams.

Analyzes healthcare claims, provider reimbursement, QPA, and dispute data to support No Surprises Act negotiations, arbitration, and OON liability management. Builds SQL-based reports, dashboards, data processes, and financial views; validates data quality; tracks dispute KPIs; integrates internal and external sources; and presents actionable recommendations to leadership and cross-functional stakeholders.