---
title: 'Senior Manager, Product Data Science at Snowflake'
canonical: 'https://feeny.ai/job/senior-manager-product-data-science-snowflake-menlo-park-s7pbsd0cstxy'
type: 'job'
last_seen: '2026-09-11'
---

# Senior Manager, Product Data Science at Snowflake

- **Company:** [Snowflake](https://feeny.ai/companies/snowflake)
- **Location:** Menlo Park, CA
- **Compensation:** $227k–$327k
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-06-08
- **Last confirmed live:** 2026-09-11
- **Apply:** https://jobs.ashbyhq.com/snowflake/117e5dc0-6191-43f2-8e05-863d405da289/application

**Skills:** SQL, Python, Machine Learning, Large Language Models, LLMs, Data Science, AI Evaluation Methods, Scalable Data Pipelines, Analytical Workflows

> Lead the App Experience & Marketplace Data Science team as a hands-on tech lead and manager. Drive AI-native product development, mentor data scientists, and validate AI/ML outputs while partnering with cross-functional stakeholders to optimize user experience.

## Job description

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.
- 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

## QUALIFICATIONS:

- 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.

Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee's duty to keep customer information secure and confidential. Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake. How do you want to make your impact? For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: [careers.snowflake.com](http://careers.snowflake.com)

## About Snowflake

## Company Overview
- **One-liner**: Snowflake provides an AI Data Cloud platform that enables enterprises to store, analyze, and securely share their data across multiple clouds and geographies.
- **Entity Type**: Public (NYSE: SNOW)
- **Headquarters**: Bozeman, Montana, United States
- **Founded**: 2012
- **Founders**: Not explicitly listed in the provided search results (widely known co-founders include Benoit Dageville, Thierry Cruanes, Marcin Zukowski – not verified in these search results)

## Core Business
- **Primary Industry**: Enterprise software, cloud data platform
- **Target Customers**: B2B, including large enterprises (e.g., hundreds of the world’s largest companies), mid-market, and SMBs
- **Mission**: “To Mobilize the World’s Data” (Glassdoor) and “empower every enterprise to achieve its full potential through data and AI” (Snowflake Careers page)

## Products & Services
- **Snowflake AI Data Cloud**: A unified, multi-cloud platform that combines data warehousing, data lakes, data sharing, and AI/ML capabilities. Customers can discover, share, and analyze data while running analytic workloads across public clouds (AWS, Azure, GCP).
- **Snowflake Marketplace**: A marketplace for discovering and accessing third‑party data sets and applications.
- **Snowflake‑Powered Applications**: Platform for building and deploying data‑intensive applications.

## Market Standing
- **Valuation/Market Cap**: Not directly provided in search results (as a public company, market cap fluctuates and is available on financial websites).
- **Key Metric**: Annual Revenue – $1 to $5 billion (USD) per Glassdoor.
- **Notable Investors/Partners**: Not explicitly mentioned in the search results (historically backed by Sequoia Capital, Dragoneer, etc. – not verified here).
- **Growth Signals**:
  - Named #1 on the 2023 Fortune Future 50 List ([Fortune.com](https://fortune.com))
  - Listed as a U.S. Best Large Place to Work by BuiltIn in 2024
  - Recognized as one of the “20 Coolest Cloud Software Companies” by CRN in 2022 and 2024
  - Headcount of 5,001–10,000 employees with 30 global locations; actively hiring
  - Revenue range $1B–$5B indicates strong scale

## Competitive Advantages
- **Multi‑Cloud Flexibility**: Operates across AWS, Azure, and GCP, avoiding vendor lock‑in.
- **Unified Data Experience**: One platform for data sharing, analytics, and AI, reducing silos.
- **Separation of Compute and Storage**: Allows independent scaling and cost efficiency (not detailed in provided sources, but a known differentiator).
- **Strong Ecosystem**: Data marketplace and extensive partner network.

## Strategic Focus
- **AI & Data Innovation**: The company’s current emphasis is on making “enterprise AI easy, efficient, and trusted” and integrating AI capabilities into the Data Cloud.
- **Global Expansion**: Active hiring across 30 locations indicates continued geographic growth.
- **Customer‑Centric Development**: Focus on empowering enterprises to achieve “full potential through data and AI.”

## Why Work Here
- **Culture**: Described as “driven by innovation, low egos, high bars, and collaboration” (Snowflake Careers page). Glassdoor rating of 3.9/5 overall (78% approve CEO).
- **Work‑Life Balance**: Glassdoor rates Work/Life Balance at 3.7/5; many remote and hybrid roles available (see Indeed listings).
- **Benefits**: “Benefits & Beyond” program includes competitive compensation, equity, career advancement programs, and commitment to pay equality and veteran hiring.
- **Engineering Focus**: Hiring process includes 2–4 week timeline with technical interviews; the company values impactful, project‑based work for all roles, including interns.
- **Recognition**: Named a Best Large Place to Work (BuiltIn 2024) and future‑focused by Fortune, signaling strong employer brand.

## Sources
1. [Snowflake Careers Overview](https://careers.snowflake.com/us/en)
2. [Life at Snowflake](https://careers.snowflake.com/us/en/snowflake-life)
3. [Snowflake on Glassdoor](https://www.glassdoor.com/Overview/Working-at-Snowflake-EI_IE928471.11,20.htm)
4. [Snowflake Hiring Process](https://careers.snowflake.com/us/en/gethired)
5. [Snowflake on Indeed](https://www.indeed.com/cmp/Snowflake-7f4a7fba)
6. [Snowflake Careers Portal (Ashby)](https://jobs.ashbyhq.com/snowflake) – provided by user

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