Top Remote Analytics Jobs in San Francisco Bay Area, CA

Analyze sales, marketing, and customer success performance, including pipeline, funnel conversion, campaigns, retention, and revenue drivers. Build and maintain dbt models and marts using Salesforce and modern data-stack tools, while owning data quality and documentation. Contribute to Lighthouse, a BI-as-code platform, and develop AI-assisted analytics workflows. Partner with stakeholders to frame ambiguous questions, deliver recommendations, and communicate progress in two-week sprints.

Analyze Talent Acquisition and people data to identify hiring trends, bottlenecks, quality issues, and equity opportunities. Partner with recruiting and business leaders to translate ambiguous questions into rigorous analyses, validate data, monitor metrics, and deliver actionable recommendations. Lead analytics projects end to end while using storytelling, product management, design thinking, and data-driven iteration to improve employee and candidate experiences.

Lead pricing analytics for merchant/platform deals and international market expansion. Define pricing strategy, run economic analyses, design and test pricing constructs, and collaborate with product, partnerships, credit, finance, capital markets, and engineering to optimize portfolio performance.

Inovalon seeks candidates to join their Talent Community, emphasizing data-driven solutions to enhance healthcare outcomes and economics.

Lead strategic revenue cycle analyses to diagnose patient billing and collections performance, quantify ROI and value, build executive-ready recommendations and playbooks, partner cross-functionally, and mentor teammates to drive scalable, data-driven improvements.

Own the end-to-end analytical function for a core business area such as growth, product, AI and automation, or strategic partnerships. Define business problems and metrics, build reports, analyze data, design experiments, surface insights, and drive recommendations through execution. Partner with product, growth, finance, and operations leaders to influence decisions and improve key business outcomes.

Own the analytical function for a core business area such as growth, product, AI and automation, or strategic partnerships. Define business questions, metrics, reports, analyses, and experiments; surface actionable insights; influence leadership decisions; and drive initiatives through execution. The role requires first-principles problem solving, strong data skills, persuasive communication, and end-to-end ownership of ambiguous business problems.

Lead data-driven initiatives by partnering with marketing, product, and BD to inform acquisition and partnership strategies. Design, run, and analyze A/B experiments, leverage machine learning for in-depth analyses, test growth levers, and automate manual processes to improve operational efficiency.

Partner with cross-functional teams to drive data-driven growth: design and analyze A/B tests, leverage machine learning for insights, define acquisition and partnership levers, and automate processes to improve operational efficiency.

Partner with marketing, product, and biz-dev to drive data-driven growth. Design, run, and analyze A/B tests, define acquisition and partnership levers, leverage machine learning for insights, and automate operational processes to improve efficiency and scalability.

Lead end-to-end research and production pipelines for systematic trading strategies. Conduct alpha research using statistical and ML techniques on high-frequency tick and order-book data, build Monte Carlo simulations and real-time risk monitoring, design position-sizing and stress-testing frameworks, mentor junior researchers, and collaborate with trading and infrastructure teams to deploy production-grade models and risk controls.

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.

Own paid social measurement and analytics across brand, consideration, and performance campaigns. Execute Conversion Lift and Brand Lift Studies, design geo-randomized experiments with data science, build KPI dashboards, evaluate creative and audience performance, and recommend budget and strategy changes. The role requires advanced SQL and Python or R, causal inference expertise, scalable reporting, and the ability to communicate insights to senior marketing leaders.

Lead current-year and long-term AP volume forecasting using statistical and AI/ML methods; diagnose supply-demand drivers; close analytic data gaps; translate analyses into strategic recommendations; mentor staff and communicate forecasts and risks to senior stakeholders across College Board.

The Senior Data Scientist will build frameworks for data-driven decision making, develop predictive models, ensure data quality, and enhance customer experiences through analytics and operational insights.

Provide geospatial and market intelligence to support leasing, marketing, investments, and development. Maintain geospatial datasets and trade areas, perform location-based analyses integrating internal and third-party data, build maps/dashboards/reports, and apply AI-enabled tools and automation to improve research, reporting, and decision support across the organization.

Lead people-analytics strategy for Talent Acquisition and Talent Development. Drive end-to-end analysis of complex workforce problems, deliver evidence-based recommendations to senior leaders, ensure data governance and quality, coach junior analysts, build metrics frameworks, and conduct benchmarking and external research to inform workforce strategy.

Advances the firm’s clinical analytics platform, translating pharmacy and utilization-management expertise into scalable analytical frameworks. Partners with financial, analytics, clinical, and payer teams to standardize insight generation, validation, and communication. Develops pharmacist training, mentorship, educational materials, and enterprise clinical guidance while supporting specialty-drug, medical-pharmacy integration, and outcomes-focused strategy.

Own the analytical function for a core business area such as growth, product, AI and automation, or strategic partnerships. Define business questions, metrics, reports, experiments, and analyses; surface insights; make recommendations; and drive decisions and execution with cross-functional stakeholders. The role requires independently structuring ambiguous problems, interpreting data, communicating persuasively with leadership, and delivering measurable business impact.

Lead analytical efforts in Real World Data research, develop specifications and methodologies, manage projects, and communicate findings to stakeholders.

The Lead Risk Analytics Data Scientist will develop risk pricing, design data models, automate workflows, and communicate insights to leadership. Responsibilities include owning the risk narrative, building analytics foundations, and utilizing AI to enhance efficiency.

Lead supply-and-demand forecasting for the psychiatry service line: build and maintain S&D models, integrate models into core data infrastructure, define operational metrics (capacity, clinician utilization, hiring targets), run forecast vs. actual audits, and partner cross-functionally to guide hiring, resource allocation, and operational improvements.

Lead MyFitnessPal’s product analytics practice and team, advising the Chief Product Officer and senior leaders through actionable data insights. Define product metrics, oversee experimentation, analyze customer and marketing behavior, improve instrumentation and data infrastructure, and shape product strategy, roadmaps, engagement, and retention. This hands-on director role combines executive communication, team development, analytical leadership, and direct analysis across consumer iOS and Android applications.

Analyzes healthcare claims, provider, reimbursement, and financial data to support out-of-network dispute negotiations, arbitration, QPA accuracy, and IDR performance. Builds SQL-based reports, dashboards, data processes, metrics, and financial views; validates data quality; integrates internal and external sources; identifies trends and risks; and presents actionable recommendations to leadership and cross-functional stakeholders.

Own end-to-end product and customer analytics across financial product experiences. Define meaningful metrics, analyze complex datasets with SQL, connect customer behavior to business outcomes, and translate qualitative feedback into product insights. Partner with product, engineering, research, data science, and CX teams to influence roadmaps and senior leadership decisions. Use AI tools such as Cursor and Claude to accelerate analysis and automate workflows.