Mehdi Zemni is a Senior Data Scientist based in Paris with seven years of experience building and deploying machine learning and computer vision systems across industry and research. Trained at CentraleSupélec and ENS Paris-Saclay (MVA) with a stint at NUS, he blends strong mathematical foundations with hands-on work in generative models, counterfactual explanations, and anomaly detection. His work spans academia-quality research—coauthor of OCTET (CVPR'23) and accompanying code at Valeo.ai—to product-focused roles delivering production ML at Criteo and IRIS by Argon & Co. He has tackled diverse problems from satellite/aerial anomaly detection to financial factor modeling and image editing/super-resolution, showing an unusual ability to move ideas from papers to production. Colleagues describe him as both research-savvy and pragmatically product-minded, with a personal portfolio (mzemni.com) showcasing projects that bridge theory and applied impact.
7 years of coding experience
3 years of employment as a software developer
Engineering, applied mathematics & Data science, GPA: 4.0, Engineering, applied mathematics & Data science, GPA: 4.0 at CentraleSupélec
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