Top Data Science Jobs in San Francisco Bay Area, CA

The Data Scientist will build machine learning models to enhance claim audits, optimize performance, and improve healthcare decision-making by analyzing complex data sets.

As a Senior Data Scientist, you will solve machine learning problems in payment risk and build end-to-end ML solutions impacting business. Responsibilities include data analysis, model deployment, and collaboration with teams.

The Data Scientist will build and deploy machine learning algorithms, conduct A/B testing, collaborate across teams, and optimize applications for growth marketing.

As a Staff Data Scientist, you will analyze data to guide product strategy, develop A/B testing frameworks, and create metrics for success in collaboration with product teams.

As a Data Scientist, you'll analyze viewer behavior and monetization, create insights and dashboards, maintain complex queries, and collaborate on data science efforts.

As a Data Scientist, you will develop data-driven solutions, create visualizations, and support data integration for energy projects applying machine learning and AI techniques.

The Data Scientist will analyze data to enhance business performance, engage customers, and optimize product strategies through experimentation and metrics establishment.

The Bioinformatics Data Scientist will analyze data, build pipelines, evaluate tools, and collaborate on product development to enhance DNA synthesis innovations.

As a Staff Data Scientist, you will design and interpret experiments, mentor others, and communicate findings to influence product development and marketing strategies.

As a Data Scientist, you will define metric goals, create dashboards for stakeholders, manage data pipelines, and optimize data solutions.

The Data Scientist will design scalable data pipelines, develop core metrics, create dashboards, analyze experiments, and communicate insights to stakeholders.

The Data Scientist IV leads machine learning model development, performs data analysis for insights, collaborates on projects, and mentors junior team members.

The Senior GTM Data Scientist will design and deploy predictive ML systems that enhance customer acquisition, sales efficiency, and retention. Responsibilities include building models, defining product vision, and architecting data foundations, all while ensuring model impact on revenue.

The Data Scientist II role involves developing scalable analysis frameworks, building monitoring systems, enhancing data pipelines, and facilitating model improvements for customer success while collaborating across teams.

The Data Scientist will develop tools for enhancing signature management capabilities, integrate diverse data holdings, and leverage AI/ML solutions for operational support.

As a Data Scientist at Sardine, you'll design and deploy data-driven solutions to prevent fraud, collaborating with clients and engineering teams to build and optimize machine learning models.

Join as a Data Scientist II to develop AI systems for biomedical research, focusing on LLMs and computer vision, while collaborating with researchers.

As a Data Scientist at Sleeper, you will analyze user behavior, build analytics systems, and develop risk insights to improve user experience and integrity on the platform.

As a Data Scientist, you will own analytical projects that influence product decisions and marketing campaigns. You'll apply statistical methods and predictive modeling to enhance customer value and drive business outcomes, collaborating cross-functionally to integrate insights into strategies.

The Staff Data Scientist will advance machine learning models to optimize claim audits and improve business outcomes in healthcare.

The Staff Data Scientist will lead the development and deployment of ML and GenAI systems to detect billing errors and fraud in healthcare payments, collaborating with cross-functional teams.

Partner with product engineering to design and analyze experiments, apply causal reasoning and statistical modeling to marketplace data, and drive data-informed product decisions across the engineering org.

Own end-to-end data science and ML work for B2C customers: build recommendation, forecasting, segmentation, and activation models; design A/B tests and causal analyses; create configurable multi-tenant model architectures; extract signal from sparse/noisy data; partner with engineering to productionize models and deliver analyses that change business decisions.

Lead and own the data science function: design and build production ML systems (recommendation, forecasting, segmentation), develop configurable multi-tenant models, run rigorous experimentation and causal analyses, connect model outputs to business impact, set scientific standards, and hire and mentor a high-velocity data science team.

The job involves supporting data-driven initiatives, performing analyses, building data models, and collaborating with product teams to enhance user engagement and improve business outcomes.