• 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.