Tommaso Ferracci is a product-focused Senior Data Scientist at Wise with a strong track record in fincrime and AML model development. Over four years he has combined rigorous academic training in statistics and physics with hands-on experience building scalable ML pipelines, from energy-reconstruction models for particle physics to targeted data augmentation techniques at American Express. He specializes in mathematically challenging problems—designing novel hardness characterizers and leveraging generative models to improve sample efficiency and model robustness. Tommaso is pragmatic about production constraints, routinely optimizing GPU-accelerated training and Big Data workflows while keeping a clear product impact lens. Based in Stony Stratford, he brings both high academic distinction and a proven ability to translate research ideas into measurable gains in operational risk systems.
4 years of coding experience
1 year of employment as a software developer
Bachelor of Science - BS, Physics, 110/110 cum Laude, Bachelor of Science - BS, Physics, 110/110 cum Laude at Università degli Studi di Padova
Master of Science - MS, Statistics (Data Science), Distinction, Master of Science - MS, Statistics (Data Science), Distinction at Imperial College London
London School of Economics and Political Science
Maturità Scientifica, 100/100 cum Laude, Maturità Scientifica, 100/100 cum Laude at Liceo Scientifico Galilei - Belluno
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