Design, validate, and deploy robust, scalable optimization frameworks and distribution models to ensure complete mathematical integrity across downstream metrics.
Explore and execute complex methodologies, evaluate methodological trade-offs, and implement advanced statistical procedures.
Partner cross-functionally to transition ad hoc code into standardized, version-controlled templates and logical libraries to ensure analytics are structured cleanly to power diverse product surfaces.
Partner closely with Data Engineering to optimize code performance and scale analytical workflows, helping transition complex statistical calculations from standard database queries into efficient, production-grade cloud compute architectures.

4–5 years of professional data science experience
2-3 years of experience with an advanced degree
Bachelor’s degree in a highly quantitative field (Statistics, Economics, Physics, Mathematics, Engineering, or a related discipline)
A Master’s degree is strongly preferred
Exceptional expertise in working with, modeling, and optimizing for statistical distributions
Advanced proficiency in Python or R
Expert-level SQL
Direct experience working with panel data or longitudinal consumer data (Big Plus)
Hands-on experience analyzing receipt data or transaction-level consumer data (Big Plus)
Experience working with Databricks and scaling advanced compute workloads (Big Plus)

Data Scientist

Key skills