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