Antonio Trenta is a Senior Associate AI/ML Engineer based in London with 12 years of experience building practical data-driven products across finance, publishing, and e‑commerce. Trained in statistics and machine learning (MSc UCL, top mark in Statistics), he is a data science generalist who learned to code on the job and focuses on Recommender Systems, anomaly detection, NLP and analytics. His recent work at JPMorgan and Elsevier spans production-grade personalization, bot and anomaly protection, entity linking and fairness-aware recommenders that balance utility with societal considerations. A pragmatist and proponent of the KISS principle, he combines rigorous quantitative thinking with product-focused experimentation to deliver measurable KPIs such as retention and forecasting. Notably, he bridges research and engineering—prototyping new algorithms early and operationalising them at scale—making him effective at turning complex models into reliable business impact.
Master's degree, Statistics, 110/110, Master's degree, Statistics, 110/110 at Università degli Studi di Roma 'La Sapienza'
Master of Science (MSc), Machine Learning, Distinction, Master of Science (MSc), Machine Learning, Distinction at University College London, U. of London
Contributions:22 commits, 7 pushes, 1 branch in 7 years 7 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.