---
title: 'GTM Staff Data Scientist at Snowflake'
canonical: 'https://feeny.ai/job/gtm-staff-data-scientist-snowflake-menlo-park-4n5aswnen76j'
type: 'job'
last_seen: '2026-09-11'
---

# GTM Staff Data Scientist at Snowflake

- **Company:** [Snowflake](https://feeny.ai/companies/snowflake)
- **Location:** Menlo Park, CA
- **Compensation:** $184k–$265k
- **Employment:** full-time
- **Posted:** 2026-08-17
- **Last confirmed live:** 2026-09-11
- **Apply:** https://jobs.ashbyhq.com/snowflake/c80ed4e9-d840-47bc-ad8c-64ed1ff97826

## 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.

Our Data Analytics and AI org (DAA) is actively seeking a Staff Data Scientist, GTM to provide technical leadership for Snowflake’s next generation of AI & Machine Learning powered GTM decision systems.

You will contribute to high-impact work across sales and marketing: propensity models across the GTM funnel, measuring the causal effect of GTM investments and interventions, and recommending actions for accounts, leads, opportunities, and customers.

This role goes beyond developing models. You will define how decision systems are designed, evaluated, productionized, and integrated into the workflows of sellers, marketers, and business leaders. You will establish reusable technical standards, guide investment across use cases, and ensure that sophisticated methods translate into measurable business impact.

## What You’ll Do

- Set the technical direction for a portfolio of AI & Machine Learning GTM decision systems spanning Sales and Marketing.
- Develop pipeline forecasting methods that model stage progression, conversion, deal timing
- Build account, lead, opportunity, and customer models that identify propensity, risk, potential, and likely next outcomes.
- Develop recommendation and next-best-action systems that determine where GTM teams should focus, which action to take, and when to take it.
- Apply causal inference, experimentation, and uplift modeling to measure the incremental impact of campaigns, sales activities, and customer interventions.
- Define common standards for point-in-time training, backtesting, calibration, ranking quality, treatment-effect evaluation, uncertainty, and realized business impact.
- Partner with GTM leaders and RevOps to identify high-value decisions, define interventions, and embed outputs into recurring workflows.
- Separate genuine customer and market movement from CRM changes, selection effects, territory shifts, instrumentation gaps, and model artifacts.
- Mentor scientists and raise technical standards across GTM Data Science and its partner teams.

## What We’re Looking For

- Advanced degree in Statistics, Mathematics, Operations Research, Economics, Engineering, Computer Science, or a related quantitative field, or equivalent practical experience.
- 5+ years of experience building production-grade statistical or machine learning systems with meaningful business impact.
- A record of setting technical direction across ambiguous, cross-functional, or multi-team problem spaces.
- Deep expertise in several relevant areas, such as causal inference, experimentation, forecasting, propensity modeling, uplift modeling, ranking, or recommendation systems.
- Strong judgment about when to use predictive ML, causal methods, generative AI, or a simpler analytical approach.
- Experience translating business decisions into measurable objectives, interventions, evaluation designs, and production systems.
- Strong Python and SQL skills and experience working with large-scale data platforms.
- Experience operating models with monitoring, validation, versioning, reproducibility, and safe lifecycle management.
- Ability to work with imperfect CRM, marketing, product, and customer data while making assumptions and limitations explicit.
- Demonstrated ownership of high-stakes outputs used by business or executive stakeholders.
- Excellent communication, technical leadership, and cross-functional influence skills.

Especially Valuable Experience

- B2B SaaS, enterprise sales, consumption-based businesses, or account-based GTM motions.
- Pipeline forecasting, account prioritization, lead or opportunity scoring, expansion, renewal, or churn modeling.
- Incrementality testing, causal measurement, uplift modeling, or marketing effectiveness.
- Recommendation systems, next-best-action models, ranking, or decision optimization.
- LLMs, agents, retrieval systems, or AI-assisted Sales and Marketing workflows.
- CRM, marketing automation, product telemetry, customer success, and unstructured interaction data.
- Deploying model outputs into business workflows and measuring adoption and realized impact.

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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