Top Data Science Jobs in San Francisco Bay Area, CA

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

Embedded on a core business team, the Data Scientist defines problems, builds metrics and reports, runs analyses and experiments, and translates insights into executable recommendations to drive growth, product, AI/automation, or partnership outcomes.

Embed within a business unit to define problems, build metrics/reports/experiments, surface insights, and drive data-informed decisions end-to-end across growth, product, AI/automation, or partnerships.

The Staff Data Scientist will lead data initiatives to enhance AI algorithms, manage data curation, and collaborate across functions to evaluate model performance.

The Data Scientist will develop performance evaluation frameworks for autonomous vehicles, using statistical models and metrics to ensure quality and safety of the Waymo Driver, while collaborating with engineering teams on simulation data and product readiness.

The Bioinformatics Data Scientist will analyze multi-omics data, develop methods, build tools, and communicate findings to support drug development decisions.

As a Senior Data Scientist, you will lead high-complexity projects, develop ML and NLP solutions, and collaborate across teams to drive business impact through statistical modeling and data analysis.

As a Data Scientist, you'll manage data science projects involving ML techniques, code development in Python and PySpark, and collaborate across teams. You will mentor juniors and contribute throughout the project lifecycle from analysis to deployment.

Lead and deliver end-to-end data science projects: design, build, deploy, and monitor ML/statistical models for credit risk, pricing, collections, and fraud. Partner with cross-functional teams to integrate models into production, set model development standards, mentor engineers, and maintain reliable ML pipelines and monitoring systems.

Partner with Product and Engineering to define product metrics, design experiments and causal analyses, build reporting and models, analyze user behavior and segments, and translate insights into product recommendations while establishing Product Data Science practices.

As a Data Scientist, you'll build production-grade ML systems for HVAC efficiency, working on scaling models, database optimization, and real-time monitoring systems.

The role involves building the marketing data science function, developing metrics, dashboards, and models to analyze marketing effectiveness, and fostering a data-informed culture.

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.

The Staff Data Scientist will partner with teams to enhance Moloco's creative systems through data strategy, measurement frameworks, and product influence, ensuring competitive advantage.

Lead data science initiatives to develop and deploy AI solutions that improve business outcomes. Collaborate with cross-functional teams to analyze data, create models, and evaluate performance.

Conduct data science research on experimental methodologies and causal modeling, develop tools to analyze experimental data, prototype improvements to platform features, and communicate results to internal teams and external stakeholders to drive product and research decisions.

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.

Senior individual contributor who drives product analytics, experimentation, and applied modeling. Owns growth and performance analyses, designs experiments with robust statistical evaluation, builds repeatable reporting, and partners with Product, Engineering, Operations, Clinical, and Finance to translate data into actionable product and operational decisions.

Assist senior data scientists with data collection, preprocessing, cleaning, and basic statistical analysis. Support model development, perform basic visualizations, and document processes and findings while learning and applying data science techniques.

Lead Oracle-focused healthcare data quality and analytics: validate transactional data, build standardized KPIs and dashboards, develop predictive inventory and revenue cycle models, and collaborate with clinical and finance teams to ensure compliance and optimize operations.

Build and deploy predictive and time-series models using HR and clinical data (Oracle HCM, GCP) to forecast staffing, identify flight-risk employees, analyze pay/burnout relationships, and create interactive dashboards and analyses to inform HR strategy and operational workforce decisions.

Turn multi-model signals into measurement, forecasts, and optimizations. Clean and label large datasets, extract structure with LLMs/NLP, define product-grade metrics, run experiments, build predictive models, create evals and monitors, and translate insights into product and business decisions.

Perform data cleansing, ETL, and preprocessing; analyze Retail CPG sales, inventory, and customer data; build predictive models for forecasting and segmentation; research and deploy Agentic frameworks and intelligent agents; produce visualizations and communicate insights to cross-functional stakeholders to optimize supply chain, marketing, and customer experience.

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.

As a founding Data Scientist/Machine Learning Engineer, you'll develop AI/ML models, enhance product capability, and drive impactful user outcomes while working closely with product teams.