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 and operating production-grade statistical, forecasting, econometric, or machine learning systems with meaningful business impact. Staff candidates will also have a track record of setting technical direction across broad or multi-team problem spaces
Strong hands-on experience with business-critical forecasting, driver-based or unit-economics modeling, financial planning, demand or capacity planning, or other systems that connect operational inputs to business outcomes
Deep modeling skills, including strong judgment around time-series forecasting, causal inference, panel or cohort methods, segmentation, hierarchical or probabilistic models, and when a simpler approach is more reliable than a more sophisticated one
Ability to work with imperfect or limited telemetry, define defensible assumptions, identify and close data gaps, and distinguish true business movement from instrumentation changes, one-time events, timing shifts, and model artifacts
Strong proficiency in Python and SQL, with the ability to manipulate large data sets, build models, develop reproducible analyses, and productionize them efficiently
Experience working with large-scale data systems and modern data platforms such as Snowflake, BigQuery, Redshift, or Spark
Strong systems thinking, including experience with monitoring, validation, anomaly detection, versioning, reproducibility, backfills, and safe model or pipeline changes in production
Demonstrated ownership of high-stakes outputs used by executive or business stakeholders, including the ability to respond quickly and effectively when data, models, or assumptions change
Excellent communication and influence skills, with a track record of leading through ambiguity, explaining complex relationships and uncertainty, mentoring others, and elevating technical standards across a team
Modeling or forecasting in a consumption-based, usage-based, or hybrid SaaS business
Experience with executive-facing product finance, multi-year planning, revenue forecasts, or business review systems
Experience using product telemetry, workload or feature attribution, customer cohorts, migrations, or use cases to explain and forecast business outcomes
Experience building self-service scenario tools, analytical applications, or decision products used in recurring planning and operating cadences
Experience mentoring scientists and shaping shared modeling, experimentation, data-quality, or production standards
What Success Looks Like
In this role, success means Snowflake leaders can trace revenue forecasts to a small set of measurable product and business drivers, understand why results changed, and run credible scenarios without bespoke analyst support. You balance modeling sophistication with business practicality, scale a common framework across categories without forcing false uniformity, and operate systems that are accurate, explainable, monitored, versioned, and trusted. Over time, the models become a durable operating mechanism for product prioritization, go-to-market accountability, and financial planning
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