Top Analytics Manager Jobs in San Francisco, CA

Own enterprise analytics audits, implementations, data quality, attribution, segmentation, SQL analysis, BI dashboards, experimentation measurement, and client reporting. Serve as the senior analytics partner for major accounts, present insights to executives, train client and internal teams, and help define analytics and experimentation services. The role requires hands-on Adobe expertise, autonomous prioritization, technical collaboration, and the ability to connect organic and AI search performance to pipeline and revenue.

Lead global Customer Success analytics strategy, architect data and health/adoption models, oversee data pipelines, deliver executive-level storytelling, mentor an analytics team, and drive cross-functional KPI alignment and self-serve BI adoption.

Manages financial analytics and product delivery for pharmacy benefit clients, including RFPs, procurement projects, renewals, market checks, PBM contract reviews, financial modeling, reporting, and presentations. Analyzes pharmacy spend, utilization, trends, and cost drivers using proprietary tools and Excel. Leads peer reviews, manages project timelines, improves processes, and mentors and trains financial analysts and new employees.

Lead development, validation, deployment, and quality control of advanced analytics and ML solutions for fraud detection, waste and abuse, investigative analysis, and program integrity. Provide technical leadership, translate stakeholder requirements, mentor team members, and ensure models are explainable, defensible, and production-ready.

Lead a small AI engineering team as a player‑coach: write production code, set technical direction for AI-driven analytics, build natural language data experiences, and establish eval-driven development. Own end-to-end delivery, data modeling, multi-tenant access patterns, and measurement pipelines while hiring, mentoring, and partnering with product to ship iterative, trustworthy AI features.

Build and own HRBP analytics: deliver dashboards, predictive models, ROI and program evaluation, AI-enabled workflows, data storytelling for executives, and scalable reporting systems while partnering with HRBP Operations and stakeholders.

Lead a small analytics team (staff data scientist + two analysts) to deliver curriculum, product, and program insights. Split time between people management (60-70%) and hands-on analysis (30-40%), advance experimentation and measurement, build AI/LLM-driven agentic workflows, manage sprints and cross-functional stakeholder relationships, and drive analytics that inform curriculum, product, and intervention strategies.

Own the analytical function for a business unit across growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; generate insights; make recommendations; and drive decisions through execution. The role requires independently structuring ambiguous problems, using SQL or Python, communicating findings clearly, influencing senior stakeholders, and delivering measurable business impact.

Own the end-to-end analytics function for a business area such as growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; surface insights; and recommend actions that improve key outcomes. Partner with product, growth, finance, and operations leaders to influence decisions and drive execution. The role requires first-principles problem solving, strong analytical skills, independent data work, clear communication, and ownership of ambiguous initiatives.

Own the analytical function for a business unit spanning growth, product, AI and automation, or strategic partnerships. Define business questions, metrics, reports, analyses, and experiments; generate actionable insights; and drive recommendations and decisions with cross-functional stakeholders. The role requires independently structuring data, solving ambiguous problems, communicating findings clearly, and delivering measurable business impact.

Own the analytical function for a core business area such as growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; surface insights; make recommendations; and drive decisions and execution with cross-functional stakeholders. The role requires strong first-principles thinking, independent data work, persuasive communication, and ownership of ambiguous, high-impact initiatives.

Lead and grow a team of analytics engineers while remaining hands-on with SQL, dbt, and Snowflake. Own roadmap and semantic layer development, build trusted, governed data products, partner with cross-functional stakeholders, champion data quality and observability, and hire and coach engineering talent to deliver scalable analytics and AI-ready foundations.

Translate web and marketing behavior data into actionable insights: measure website and marketing performance, analyze funnels and journeys, design and evaluate A/B tests, build reports and dashboards, monitor analytics integrity, and partner with cross-functional teams to define measurement and optimization opportunities.

The Senior Manager, Data Science & Analytics will lead the analytics strategy for client engagement, focusing on data-driven insights and marketing performance to assist in customer acquisition efforts.

Lead paid media analytics for performance marketing: build SQL-based reporting and Power BI dashboards, validate agency/platform data, run deep-dive diagnostics across paid channels, support experimentation and MMM inputs, and provide actionable media investment recommendations to improve lead quality and enrollment outcomes.

Own and build customer health, usage/adoption, and product configuration data models. Produce ad-hoc and recurring analyses to identify upsell/expansion opportunities, partner with CS, Sales, Product, and Data teams, and present actionable insights to leadership to drive revenue-relevant actions.

Own customer-facing analytics and reporting for a voice AI healthcare product. Lead customer data implementations, troubleshoot ingestion and mapping issues, prepare internal teams for campaign execution, develop dashboards, define performance metrics, and standardize reporting. Coordinate data and QA engineers through agile delivery while scaling onboarding workflows, improving implementation velocity, and expanding analytics capabilities for payer and provider customers.

Lead marketing AI deployment and measurement: identify and prioritize AI opportunities, manage cross-functional rollouts, build attribution and KPI reporting in Power BI, improve data architecture and quality, run journey and lead-scoring analyses, and shape GTM tools and processes to optimize pipeline and revenue.

Own and scale the finance and accounting data ecosystem: design and maintain BigQuery integrations, ensure data integrity and governance, build reconciliations and automated controls, develop scalable reporting and dashboards, support monthly close, forecasting, budgeting, and automate finance processes to improve visibility and efficiency.

Leads strategic sales analytics projects and delivers data-driven insights to improve acquisition, conversion, funded outcomes, ROI, and portfolio performance. Analyzes sales funnels, customer segments, campaigns, workforce capacity, and business metrics. Builds dashboards, scorecards, forecasts, and performance reports while partnering with Sales, Marketing, Risk, Product, and Operations. Presents recommendations to leadership and manages project scope, timelines, risks, and stakeholder communications.

Own product performance analytics across acquisition and engagement journeys. Responsibilities include recurring funnel and channel reporting, customer journey analysis, anomaly and root-cause investigation, impact sizing for product and data issues, forecasting and variance analysis, dashboard and measurement framework development, and ad-hoc analysis. The role partners with Finance, Product, Credit, Risk, Fraud, and other stakeholders to translate findings into actionable business recommendations.

Lead identification and quantification of issuance leakage across acquisition, application, approval, and funding funnels. Analyze digital customer journeys and conversion gaps, run root-cause diagnostics, design experiments, build executive dashboards, and translate findings into prioritized, quantified business recommendations partnering with Product, Marketing, Credit Risk, Operations, and Engineering.

Own and execute marketing operations and analytics: manage martech systems and integrations (Marketo, 6sense, webinar tools), build and QA campaigns, develop reporting and Power BI dashboards, analyze funnel and ABX performance, refine attribution and scoring, and create scalable workflows, documentation, and enablement for global and regional teams to drive measurable GTM improvements.

As a Revenue Analytics Manager, you will own reporting for Sales, Marketing, and Customer Success, build dashboards, automate workflows, and ensure data quality.

Lead analytics for Community Marketing programs: define measurement frameworks, build Power BI dashboards, run analyses across referrals/events/COI, deliver executive insights, forecast leads/opportunities, and partner cross-functionally to optimize program performance and reporting.