I turn ambiguous business questions into rigorous causal answers.
With 10+ years in data science at companies like Coinbase, Uber, Glovo, and Preply, I specialize in experimentation, causal inference, and marketing measurement — building the frameworks that let teams know what's actually driving results. My work spans end-to-end: from designing incrementality tests and synthetic control models to productionizing ML pipelines and automated analytics infrastructure. I've improved campaign ROI from 1.1x to 6x, reduced incremental acquisition costs by 23%, and built experimentation systems that accelerated decision time by 4x. I care about rigorous methodology, scalable systems, and insights that move the needle.
