Top Analytics Manager Jobs in San Francisco, CA

Lead forecasting methodology and analytical strategy for warranty claims across product categories. Build predictive and financial models, translate operational data into actionable plans, partner with Finance and cross-functional leaders, produce executive reporting, improve reporting processes, and develop team capabilities through coaching and succession planning.

Lead GTM analytics and revenue operations by analyzing campaign, funnel, pipeline, and attribution performance; building dashboards; optimizing marketing technology and data quality; improving lead management, routing, scoring, and sales handoffs; and establishing scalable workflows and governance. The role partners cross-functionally with Marketing, Sales, Finance, Product, and Customer Success to support forecasting, planning, leadership reporting, and data-driven revenue growth.

Own the analytical function for a core business area, defining business questions, metrics, reports, analyses, experiments, and recommendations. Partner with product, growth, finance, and operations leaders to drive decisions and measurable outcomes. The role requires solving ambiguous problems, independently structuring and interpreting data, communicating insights persuasively, and executing initiatives end to end.

Own the analytical function for a business unit spanning growth, product, AI and automation, or strategic partnerships. Define business problems and metrics, build reports, analyze data, design experiments, generate insights, influence leadership decisions, and drive initiatives through execution. The role requires strong first-principles thinking, independent data skills, persuasive communication, and ownership of ambiguous, high-impact problems.

Own the digital measurement ecosystem across websites, quote engines, customer portals, and account applications. Lead Google Tag Manager tracking frameworks, data-layer standards, Google Analytics 4 configuration, conversion events, attribution, funnel analysis, experimentation measurement, data-quality audits, and analytics governance. Partner with Marketing, Product, Engineering, and Data teams to translate customer behavior into actionable insights that improve growth, conversion, and customer experience.

Lead design, administration, governance, and analytics of sales incentive plans for Retail Branch and Business Banking. Translate executive strategy into measurable objectives, deliver performance reporting and strategic analytics, support decision-making with financial modeling, and ensure compliance, data integrity, and audit readiness across incentive programs.

Lead analytics for the Credit Card portfolio, partnering with Product, Engineering, Credit Risk, Fraud, and Marketing to deliver data-driven strategy. Perform ad-hoc and cohort analyses, design A/B tests, manage BI reports, drive portfolio growth and risk insights, and build scalable data solutions with Data Engineering. Influence executives through clear recommendations and leverage AI tools to accelerate analytics and self-service.

Serve as embedded BI lead for a divisional sales book, delivering actionable insights from syndicated and commercial data, leading opportunity analysis, training field teams, supporting Power BI reporting, and translating complex data into executive presentations to drive sales performance and planning.

Lead end-to-end category insights for strategic account chains using syndicated, retailer POS, and internal data. Develop analyses, reporting, and recommendations to drive sales and profit, partner with sales and BI, support category reviews and business planning, and present insights to stakeholders.

Serve as embedded BI partner for an assigned division, delivering actionable commercial insights from syndicated and internal data, leading opportunity analyses, training field teams, supporting Power BI reporting, and translating complex data into executive presentations to drive sales performance and program ROI.

Performs monthly actual, forecast, and budget analysis for enterprise data and analytics initiatives. Tracks financial metrics, supports strategic planning, provides business analysis and decision support to senior managers, improves financial processes, and collaborates with cross-functional stakeholders, vendors, and sourcing teams.

Lead and grow the customer analytics practice for Communications, Media & Technology clients. Define strategy and thought leadership, communicate analytics value, and lead delivery of large-scale, complex client engagements. Apply customer analytics, CRM modeling, reporting, and predictive analytics tools to drive client outcomes. Act as a senior management-consulting leader with deep client delivery experience.

Lead client-facing marketing analytics engagements using quantitative methods to measure offline and digital marketing impact. Deliver analyses, recommendations, presentations, and project-based work including Marketing Mix Modeling, Multi-Channel Attribution, Digital Analytics, Pricing & Promotion, and Demand Forecasting. Manage and grow a team and travel extensively to client sites.

Manage pricing infrastructure and strategy, maintain price books, evaluate EBITDA impact, and lead commercial integration for acquisitions and Greenfield operations. Deliver P&L variance, price mix, financial risk, and productivity analyses supporting margin improvement and Capex decisions. Partner with Operations, IT, and the AI Steering Committee on commercial systems, responsible AI governance, and AI-enabled workflow improvements. Regular travel to branches and regional operations, including overnight stays, is required.

Own Growth Marketing analytics and data operations: build and maintain full-funnel reporting, ensure data governance and attribution, manage segmentation and Pardot audiences, maintain executive BI dashboards, partner with IT and Sales Ops, direct offshore data resources, and implement AI-assisted workflows to automate analytics and QA.

Lead BI developer who owns reporting infrastructure end-to-end: SQL-based data extraction from messy sources, LookML/BI model development, dashboard standardization, stakeholder partnership, and performance marketing optimization to drive actionable insights and business outcomes.

Own the vision, roadmap, and delivery of AI and analytics capabilities for an enterprise EHSQ SaaS platform. Lead customer and market discovery, prioritize backlogs, define product metrics, and partner with engineering, data science, architecture, design, sales, marketing, and services teams. Drive AI feature launches, adoption measurement, governance, enablement, pricing, and executive communications while ensuring trustworthy, explainable, and compliant product experiences.

Leads a team delivering Customer Success reporting, dashboards, KPI frameworks, and operational analytics. Oversees reporting accuracy, data integrity, recurring metrics, workflow improvements, and automation. Partners with Customer Success and services leadership to translate business needs into analytical requirements, prioritize initiatives, standardize reporting methodologies, and communicate performance insights. Coaches analysts, manages workload and development, and supports data-driven operational decision-making and scaling.

Leads internal data analysis projects, identifies business opportunities and risks, delivers strategic insights to leadership, manages junior analysts, develops dashboards, and improves data quality across company platforms. The role requires translating quantitative findings for nontechnical audiences and applying healthcare or pharmaceutical dataset experience to strategic decision-making.

Lead financial modelling and analytics for pricing, monetization, and strategic finance. Build scenario and profitability models, apply AI/ML (LLMs, predictive models) to accelerate modelling and reporting, deliver executive-ready profitability reporting, and partner with FP&A, Sales Ops, and GTM leaders to support strategic decisions.

Lead supply chain data and systems strategy for data center projects: develop analytics and BI datasets, build KPI dashboards, manage supply chain systems (ERP/SLM/Oracle/Power BI), enforce master data management, and support cross-functional teams to enable data-driven decision-making and automation.

Lead business analytics strategy by developing dashboards, scorecards, KPIs, automated reporting, and performance measurement frameworks. Analyze sales and operational data to identify trends, risks, and opportunities, translating findings into actionable recommendations. Partner with Sales, Operations, Finance, IT, and leadership on forecasting, business cases, analytics modernization, governance, and process improvement. Communicate insights through reporting and data storytelling while mentoring analysts and leading cross-functional initiatives.

Lead and develop Analytics Engineers responsible for shared data foundations, platform capabilities, semantic models, developer tooling, and AI-enabled workflows. Define the team vision, operating model, roadmap, standards, and success measures. Partner cross-functionally to prioritize initiatives, improve adoption, guide architecture, and deliver scalable data assets and automation. Drive responsible AI-assisted development, data reliability, testing, documentation, observability, and cost management while contributing hands-on when needed.

Lead commercial analytics to measure ROI, uncover growth opportunities, and deliver actionable insights. Build dashboards, perform SQL-based analyses, improve data quality, support forecasting, and implement automation/AI to streamline workflows. Partner cross-functionally with Sales, Marketing, Finance and Strategy to influence revenue and retention decisions.

Leads and scales a global data engineering and analytics team while remaining hands-on with architecture, pipelines, data quality, dimensional modeling, dashboards, reporting, and customer-facing deliverables. Owns the analytical data platform supporting clinical, operational, product, financial, and customer data. Partners with cross-functional stakeholders, investigates complex data issues, improves platform reliability and security, and mentors engineers.