Summary
Luca Pozzi is a senior machine learning scientist in San Francisco with nine years of applied experience building causal inference and experimentation platforms for leading internet companies including Netflix, Meta (Facebook AI), and Uber. He combines a Ph.D. in Biostatistics from UC Berkeley with hands-on engineering—shipping production-grade Python and Spark systems for measuring incrementality, counterfactual evaluation, and synthetic control at scale. Luca has repeatedly translated cutting-edge causal methods into operational tooling that informed ads ranking, marketing spend, and retention strategies, and he evangelizes measurement practices across product teams. His background spans both high-impact industry deployments and academic research in dimensionality reduction and loss-based estimation, and he often builds complex simulations and Linux-native tooling regardless of programming language. This blend of rigorous statistics, systems engineering, and product-oriented measurement makes him a go-to expert for trustworthy, scalable causal analytics.
9 years of coding experience
11 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Biostatistics with Designated Emphasis in Computational Sciences and Engineering, Doctor of Philosophy (Ph.D.), Biostatistics with Designated Emphasis in Computational Sciences and Engineering at University of California, Berkeley
Bachelor of Science - BS, Mathematics, Bachelor of Science - BS, Mathematics at Politecnico di Torino
Italian, English, French, Spanish