Own and evolve business-critical data products, designing scalable data services, APIs, models, and batch or streaming pipelines. Lead projects through implementation, deployment, monitoring, and production support while applying AI tools throughout the software development lifecycle. Collaborate across engineering, product, data, and business teams, contribute to architecture and governance, improve reliability, and mentor earlier-career engineers.

Lead development of scalable econometric and causal-inference methods (DiD, RDD, IV, synthetic controls, panel data) to measure long-term marketplace impact. Integrate causal insights into production ML systems, influence product strategy, present findings to executives, and mentor data scientists and economists.

Lead end-to-end people analytics projects, translate business priorities into analytics strategies, build metrics and visualizations, partner with HR and product teams, scale models with ML, automate analytics, and upskill stakeholders to drive org effectiveness and business impact.