Top Data Science Jobs in San Francisco Bay Area, CA

The Data Scientist will build predictive models, design data pipelines, conduct analyses, and deploy solutions in a collaborative environment.

The Staff Data Scientist will identify AI opportunities, develop machine learning models, and provide mentorship while delivering business solutions using data analytics and AI technologies.

Technical lead for Growth Analytics: partner with Growth/Marketing/Sales to identify opportunities, design experiments and statistical models, build scalable measurement frameworks, mentor junior data scientists, translate business questions into analytic solutions, and communicate insights to drive acquisition, activation, retention, and reactivation.

As a Staff Data Scientist at Gusto, you will drive data-informed decision-making, lead projects, collaborate with teams, and mentor others in statistical analysis and experimentation.

Lead end-to-end direct mail marketing campaigns: define targeting and suppression logic, execute and validate data pipelines, manage offshore execution, measure ROI and experiment results, partner with marketing and third parties to optimize audiences and campaign performance, and present insights to senior leadership.

Lead measurement and decision systems for patient growth: own incrementality, design experiments, build LTV/retention/forecasting models, create trusted marketing metrics, partner with Engineering for measurement plumbing, diagnose performance shifts, influence channel allocation, and mentor growth analytics teams.

Lead product measurement strategy and complex evaluation for major product areas. Own experimentation standards, design causal and Bayesian analyses, build scalable measurement systems and dashboards, drive cross-team initiatives, mentor data scientists, and influence product decisions to improve mental healthcare outcomes.

As a Senior Data Scientist, the role involves leveraging data analysis, experimentation, and statistical methods to influence business decisions and enhance Gusto's product performance, while mentoring team members.

As a Product Data Scientist, you will analyze user behavior, drive experimentation, build data tools, and collaborate across teams to influence product strategy and innovation at Whatnot.

Lead product analytics to inform strategy and optimize user experience: translate business questions into analysis, build reliable analytics infrastructure, run A/B tests and ML/statistical analyses, track funnels and cohorts, support 0-to-1 product launches, and communicate actionable insights to cross-functional teams.

The role involves analyzing fraud and risk data, defining KPIs, collaborating on anti-fraud strategies, and creating tools and dashboards for data accessibility at Whatnot.

As a Data Scientist at SentiLink, you'll develop fraud detection models using machine learning, engage in product development, and support analysis across teams. This role emphasizes hands-on technical work and end-to-end project ownership in a fast-paced environment.

The Data Scientist will analyze data to provide insights, partner with teams for metrics, develop models, and create accessible visualizations to influence product and program strategies.

Partner with Digital Assets, Finance, Treasury, and Risk to design measurement frameworks, perform strategic analysis and modeling, build scalable SQL-driven automation and dashboards, analyze on-chain and finance data, create visualizations, and drive data-informed product decisions for USDC and related digital asset offerings.

Lead GTM data science initiatives to build revenue forecasting, causal inference analyses, and AI-enabled solutions that improve sales, retention, and expansion. Partner with Product, Growth, and Commercial teams to operationalize insights, communicate findings to stakeholders, and mentor junior data scientists.

Lead payments-focused data science work: build foundational datasets, metrics, and scalable analytics; analyze customer and transaction behavior (including onchain data); conduct strategic analyses to identify product and revenue opportunities; build reporting, dashboards, and automation; and influence product and business strategy through data storytelling to senior stakeholders.

As a Data Scientist at Profound, you'll build predictive models, optimize AI-driven brand visibility, and turn data insights into actionable strategies. Requires proficiency in Python, R, and SQL, with 3+ years of analytics experience.

Embedded within a core business area, own end-to-end analytics: define problems, build metrics/reports, run analyses and experiments, surface insights, and drive data-driven recommendations to influence product, growth, AI, or partnerships.

Embedded on a business unit, define problems and metrics, run analyses and experiments, build reports, surface insights, and drive data-informed decisions across growth, product, AI, and partnerships.

Embed with a business unit to define problems, build metrics, run analyses and experiments, generate insights, and drive data-informed decisions end-to-end to improve growth, product, AI automation, or partnerships.

Embedded in a core business area, you will define problems, build metrics and analyses, run experiments, surface insights, and drive data-informed recommendations end-to-end to improve product, growth, AI/automation, or partnerships metrics.

Embedded on a business unit (growth, product, AI, or partnerships) to define problems, set metrics, build reports, run analyses and experiments, surface insights, make recommendations, and drive end-to-end execution to improve key business metrics.

Embedded on a core business team, own analytics end-to-end: define problems, build metrics and reports, run analyses and experiments, surface insights, and drive data-informed recommendations to improve growth, product, AI/automation, or partnerships.

As a Data Scientist at Retool, you will analyze customer behavior and business performance, build analytical models, and provide insights to guide strategy across teams.

Lead product-focused data science at OpenArt: design experiments, build metrics and dashboards, run user and behavioral analyses, inform product and growth decisions, collaborate cross-functionally, and establish DS best practices as the first US hire.