Top Data Science Jobs in San Francisco Bay Area, CA

Lead GTM-focused data science initiatives: build revenue forecasts, apply causal inference, develop AI-enabled sales and retention solutions, partner with Product/Growth/Commercial teams, and translate analyses into scalable, automated workflows and executive-ready recommendations.

Partner with Growth, Marketing, Sales, and Product to measure and optimize marketing and growth initiatives. Build dashboards and scalable measurement frameworks, design experiments, analyze ROI and trends, provide actionable recommendations, and communicate results to technical and non-technical stakeholders.

The Data Scientist will lead efforts in measuring safety impacts of AI products, implement statistical methods, and create metrics and dashboards, collaborating with cross-functional teams.

Conduct data science research advancing experimental and causal methodologies; develop robust tools and prototypes to analyze experimental data; improve core platform features; and communicate findings to internal teams and external stakeholders to drive insights and product improvements.

As a Data Scientist, you will develop algorithms, collaborate on product requirements, and communicate data-driven insights, while enhancing product offerings and delivering actionable insights.

The Staff Data Scientist will lead data science initiatives, shaping business decisions with causal inference and advanced analytics in the Partnership, Loyalty & Pay team at Lyft, collaborating with multiple teams to drive strategic data-centric recommendations.

As a Founding Data Scientist, you will develop predictive models and optimize data infrastructure to enhance supply chain operations, focusing on shipment risk and decision-making.

As the first Data Scientist, you will build models and algorithms from scratch, impacting the company's success in optimizing insurance portfolios.

The Senior Data Scientist will leverage data insights to drive growth in lending, foster AI integration, and mentor colleagues while ensuring high-quality data reporting and visualization.

Lead development, maintenance, and monitoring of credit risk models and loss forecasts. Extract and analyze large datasets with Python/SQL, automate reporting and dashboards, perform EDA and stress/sensitivity analyses, document audit-ready model deliverables, support model governance/validation, and communicate insights to stakeholders to inform credit policy and decisioning.

As a Data Scientist in Marketing, you will enhance AI-driven marketing strategies, collaborate with teams to develop metrics, analyze marketing data, and recommend improvements for user engagement.

Senior IC for GTM analytics who builds and owns GTM data models, pipelines, and a semantic layer; runs deep analyses on funnel, conversion, forecasting, quota, and retention; partners with product data and engineering to ensure consistent data and operationalized metrics for non-technical stakeholders.

Lead end-to-end data science initiatives, developing AI solutions for personalization, marketing, and product experience while collaborating with cross-functional teams on machine learning models.

Lead measurement and experimentation for the Identity product, define metrics and frameworks, design A/B tests and causal analyses, build datasets and dashboards, quantify growth vs. abuse trade-offs, and partner cross-functionally to inform product strategy.

As a Lead Data Scientist in Fraud, you will develop, deploy, and monitor machine learning models to detect and prevent fraud, while leading a team and collaborating across departments.

Design and implement quantitative behavior metrics for autonomous vehicles, build and maintain data pipelines and dashboards, analyze large-scale vehicle logs and simulation data to identify regressions, set metric thresholds to support geofence expansion, and communicate findings to technical and non-technical stakeholders.

Lead the fraud data science strategy and deliver end-to-end ML solutions to detect and prevent fraud in real time. Build, deploy, and monitor models (including lending fraud), run advanced unsupervised analyses, design A/B tests, collaborate with Product/Engineering/Risk, and produce dashboards to track KPI performance.

Design and develop large-scale HD mapping datasets, data pipelines, and benchmarking tools. Collaborate with ML and cross-functional teams to curate data, improve model training strategies, and scale mapping and update workflows for autonomous vehicles.

The Data Scientist will build AI-driven fraud and risk systems, work with real-world data, and leverage graph techniques to improve detection and labeling. They will partner with engineering to scale data systems in the compliance domain.

The Operations Data Scientist at Kikoff will enhance operational efficiency by analyzing data, developing AI tools, and collaborating with cross-functional teams, focusing on improving customer and agent outcomes.

As a Data Scientist, you will enhance product development using analytical skills, data analysis, and cross-functional collaboration to improve customer financial security.

Seeking a Data Scientist with expertise in Full stack Development and AWS Architecture for a 3-6 month local project.

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

Embed within a core business area to own analytics end-to-end: define problems, build metrics/reports/experiments, analyze data, surface insights, and drive outcome-focused recommendations with stakeholders to improve growth, product, AI/automation, or partnerships.

Embed on a core business team to define problems, build metrics, run analyses and experiments, and drive data-informed product, growth, AI, or partnership decisions end-to-end. Surface insights, recommend actions, and own execution to improve key business metrics.