Senior Manager, Product Data Science
Lead and hands-on manage a Product Data Science team focused on app experience, marketplace, and AI-native product features. Drive AI evaluation, agentic services, and mentor team on ML/LLM best practices.
Responsibilities
- Serve as the tech lead/manager of a Data Science team in the Product organization, leveraging AI tools and functions (e.g., Cortex AI functions, Agents, CoCo) to accelerate product development and data-driven decision-making.
- Mentor team members in core DS disciplines and on the effective and governed use of generative AI tools, including establishing AI best practices and guardrails.
- Drive the team's focus toward AI-native deliverables, such as building out Agentic services, semantic views, and conducting AI evaluation for new product features, strategically shifting away from automatable work.
- Be hands-on by serving as the primary data scientist on projects, specifically focusing on validating the accuracy and output quality of AI-powered analysis and developing POCs for new AI-driven product features.
- Partner with technical and business stakeholders to not only come up with solutions to stated problems, but encourage and enable the team to develop bottoms up ideas.
- Maximize the impact of the team, by making sure the data scientists have the best and correct context, and ensuring their skill sets are properly matched to the project.
- Grow the team, when appropriate. Convince job candidates on why Snowflake, and the product data science team is an awesome place to work.
Requirements
- Masters or PhD in Math/Statistics, Engineering, Computer Science, Science or related quantitative field
- 10+ years experience as a Data Scientist
- 5+ years of experience in building, managing, and leading a high-performing data science team
- Experience in using data science to optimize the user experience
- Expert in SQL and Python
- Demonstrated experience with internal AI tools to build scalable data pipelines and drive analytical workflows
- Advanced knowledge/experience in machine learning and Large Language Models (LLMs), including the ability to critically evaluate and validate AI/ML outputs (e.g., using AI evaluation methods and understanding the limitations of AI Functions)
- Ability to communicate and influence complex ideas to cross-functional stakeholders
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