Olga Petrova is a Machine Learning Tech Lead based in Paris with nine years of experience spanning deep learning R&D, applied modeling, and AI product development. Trained as a theoretical physicist (PhD, Johns Hopkins), she brings a first-principles, research-grade approach to framing ML problems and designing robust models. At Criteo she delivered sub-10 ms serving solutions for extremely noisy, high-cardinality ad datasets, achieving the first sizable uplift over longstanding logistic and GBDT baselines. Her career blends hands-on engineering and product ownership—from building ML PaaS ideas and a smart data annotation platform to consulting startups on end-to-end ML strategy. She excels at technical communication, translating complex methods for engineers, product teams, and non-technical stakeholders alike. An unexpected strength is her track record of turning physics-inspired model insights into production-ready systems that scale.
9 years of coding experience
8 years of employment as a software developer
Deep Learning a 5-course specialization by deeplearning.ai, Deep Learning a 5-course specialization by deeplearning.ai at Coursera
Johns Hopkins University
Bachelor of Science (B.S.) Physics, Bachelor of Science (B.S.) Physics at Worcester Polytechnic Institute
Product Manager Nanodegree, Product Manager Nanodegree at Udacity
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Olga Petrova - Machine Learning Tech Lead at Criteo