Product Data Science Manager

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.

We’re looking for a Senior Manager to lead our App Experience & Marketplace Data Science team in the Product organization.

You will lead a team covering app experience (UI, growth platform, analyst/admin/data engineer tools and experience) and data marketplace areas.

• Well designed high value apps are essential to make it simple for our customers to complete billions of SQL queries, deploy python, and use powerful AI tools every day

• Data marketplace makes it easy with a click of a button to get access to a wide range of 3rd party data instead of having to contact a sales representative at a data vendor and setup and maintain a complex API.

All the projects above allow the data scientist to work on very large datasets, and a variety of diverse interesting projects that span the domains of data engineering, analytics, statistics, and machine learning.

In this role, you will both lead a team, and be hands-on as a tech lead in this area. The manager will interact frequently with senior management, product managers, and engineering managers. The ability to effectively communicate complex technical ideas to a wide audience is crucial.

IN THIS ROLE YOU WILL:

• 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.