Andres Ladino is a Lead Data Scientist based in Paris with a decade of experience building AI-driven maintenance and traffic systems for transportation operators and OEMs. He designs and deploys end-to-end machine learning solutions that drive faster, more accurate fault diagnosis and remaining-useful-life predictions for train components, directly reducing costs and improving safety across maintenance workshops. With a PhD in Automatic Control and a background in ITS research, he has led European projects involving six major OEMs and published multiple peer-reviewed papers. Andres pairs research-grade expertise (traffic simulation, platooning, real-time forecasting) with hands-on production delivery—having shipped predictive models, a reusable data-science toolbox that cut analysis time by 60%, and the ML behind RATP’s SERVAL platform. He also brings people leadership experience from consultancy roles and academia, bridging stakeholders from operators to researchers. Notably, his work spans both Python and C++ implementations, reflecting a rare combination of theoretical depth and pragmatic engineering.
11 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD Automatique Productique, Doctor of Philosophy - PhD Automatique Productique at Université Grenoble Alpes
Master of Science - Electronic Engineering Electrical and Electronics Engineering, Master of Science - Electronic Engineering Electrical and Electronics Engineering at Pontificia Universidad Javeriana
Contributions:12 PRs, 103 pushes, 11 branches in 5 years 3 months
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