Summary
Marc Pozzo is a trading surveillance analyst and data scientist with 8 years of experience building automated detection systems and applied ML for energy markets across Western Europe. At ENGIE he designs, backtests and maintains market-abuse alerts and investigates complex cases under REMIT and MAR, drawing on prior regulatory experience at CRE that contributed to a landmark €12M collusion sanction. His background spans deep learning, time-series forecasting and production tooling—from YOLO/TensorFlow computer vision projects to predictive maintenance, recommendation engines and Dash/SQL monitoring dashboards—bringing both research-grade models and pragmatic automation to operations. Fluent in Python and familiar with VB.net, R and SQL, he combines commodity market expertise (France, PT, IT, ES) with hands-on investigation and cross-functional collaboration with legal and front-office teams. An engineer by training, he has a track record of turning statistical analysis into auditable, operational controls that reduce regulatory risk.
8 years of coding experience
2 years of employment as a software developer
Master 2 (M2), Marchés et droit de l'énergie, Master 2 (M2), Marchés et droit de l'énergie at Université de Montpellier
Diplôme d'ingénieur, Diplôme d'ingénieur at EPF Ecole d'Ingénieur-e-s
Prépa PC, Prépa PC at Lycée Condorcet
Data scientist, Data scientist at Université Paris 1 Panthéon-Sorbonne