Summary
Elyas Benyamina is a data scientist with nine years of experience blending rigorous mathematical training and applied machine learning across industry and research. Trained at École normale supérieure Paris-Saclay and Université Paris Cité (top-ranked in his cohort), he has tackled problems from predictive maintenance at Merck to compliance analytics at Amazon and production ML at Criteo. His work spans computer vision, text-to-SQL with LLMs, and 3D geometry/CAD comprehension, reflecting a rare mix of theoretical depth and practical engineering. He has research experience in quantitative finance from King's College London and contributes to education as an oral examiner for elite Classe Préparatoire students. Comfortable moving models from research to product, he combines strong academic honours with hands-on solutions in high-stakes commercial environments. An interesting facet: alongside industry roles he has pursued focused graduate research stints (EPFL, OMI visits) that keep his toolbox current on state-of-the-art ML methods.
9 years of coding experience
3 years of employment as a software developer
Classe Préparatoire (MPSI-MP*), Bachelor of Science (BSc) in Mathematics and Physics, Classe Préparatoire (MPSI-MP*), Bachelor of Science (BSc) in Mathematics and Physics at Lycée Saint Louis
FMJH Excellence Scholarship, Mathematics, FMJH Excellence Scholarship, Mathematics at Université Paris-Saclay
Master's degree, MVA - Mathematics, Vision, Learning, Master's degree, MVA - Mathematics, Vision, Learning at École normale supérieure Paris-Saclay
Master, Applied Mathematics (ex Paris VII Diderot/Descartes), Rank : 1st / Highest Honours, Master, Applied Mathematics (ex Paris VII Diderot/Descartes), Rank : 1st / Highest Honours at Université Paris Cité
Graduate Research Program, Graduate Research Program at EPFL