Top Senior Level Data Science Jobs in San Francisco Bay Area

As a Distinguished Scientist at ServiceNow, you will lead AI initiatives with a focus on cutting-edge technologies like deep learning, LLMs, NLP, and conversational assistants. Collaborate with engineering and product teams, architect elegant solutions, build reusable components, influence leadership, and drive thought leadership in AI.

The Staff Machine Learning Scientist will be responsible for developing generative AI applications for healthcare, collaborating with cross-functional teams, conducting healthcare-focused research, and designing and implementing generative AI models for healthcare scenarios.

Lead a team of data professionals to focus on company growth, collaborate with cross-functional teams to develop data-driven strategies for global expansion and user growth, optimize user acquisition, retention, and monetization initiatives through data-driven insights, and shape the roadmap for data science products/platform.

Thumbtack is seeking a Senior Applied Science professional to work on search, ranking, and matching algorithms for their home care marketplace. The role involves improving customer and service provider matching, modeling complex relationships, characterizing marketplace dynamics, and building a healthy marketplace.

GoodRx is looking for a Data Science Manager to join our data team. The ideal candidate is a team player with 5+ years of experience in data science, strong skills in Python, statistical analysis, predictive modeling, and machine learning. They should have prior experience managing data scientists and exposure to data-adjacent roles in engineering. A background in the healthcare/prescription drug space is a plus.

Create and maintain dashboards, queries, and models to monitor the health of IoT products, collaborate with cross-functional teams, and contribute to the improvement of customer experience in hardware reliability and quality at Samsara.

Designs, develops, and programs methods and systems to analyze big data sources and generate insights and solutions. Interacts with teams to identify data analysis questions and issues. Cleanses and integrates large datasets from multiple sources. Identifies meaningful insights and communicates findings to managers.