Applied Scientist, Customer FinOps Intelligence

Snowflake is seeking an Applied Scientist to join the Customer FinOps Intelligence team. The ideal candidate will have a strong background in statistics, applied mathematics, or a related field, and 5+ years of experience in applied data science, quantitative research, or value engineering. The role will involve developing and maintaining peer benchmarking models, constructing peer groups, and engineering a benchmarking feature store using Snowpark and dbt. The successful candidate will work closely with field teams to ensure findings are communicated with clarity and acted upon at scale.

Requirements

• MS or PhD in Statistics, Applied Mathematics, Econometrics, Computer Science, or a quantitative field
• 5+ years of hands-on experience in applied data science, quantitative research, or value engineering
• Expert-level SQL
• Strong proficiency in Python (pandas/polars, scikit-learn, statsmodels)
• Deep experience with unsupervised ML: clustering (k-means, DBSCAN, hierarchical), PCA/UMAP, anomaly detection
• Experience designing and interpreting percentile-based benchmarks and cohort analyses at scale
• Strong communication and storytelling skills
• Comfort operating in ambiguous, greenfield environments where the methodology is yours to define

Benefits

• Generous Paid Time Off
• 401k Matching
• Retirement Plan
• Visa Sponsorship