GTM Staff Data Scientist

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