Summary
Leonardo Gómez is a freelance data scientist and applied scientist with nine years of experience building production-ready AI systems, specializing in GenAI, LLMs, ML engineering, and scalable data pipelines. Based in Luxembourg, he has led cross-functional projects in banking and automotive industries—designing RAG-enabled GenAI solutions, ML monitoring and drift detection frameworks, and multi-fidelity models for virtual tire design. His background spans industrial research and applied R&D from a PhD in Applied Mathematics to hands-on engineering at Goodyear and LIST, where he developed novel algorithms for graph and kernel methods and multi-performance optimization engines. He combines deep theoretical expertise in network-based ML and graph analytics with practical skills in Python, ETL, CI/CD and REST-deployed models to move prototypes into reliable production. Unusually, he pairs academic contributions (including scalable graph anomaly detection and network fingerprinting) with frontline delivery for regulated sectors like private banking and AML/KYC. Currently he helps organizations unlock data value through bespoke AI solutions as founder of LGsquare Consulting.
9 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy - PhD, Applied Mathematics, Doctor of Philosophy - PhD, Applied Mathematics at Université catholique de Louvain
Master of Science in Industrial and Applied Mathematics, Computer Science, Master 2, Master of Science in Industrial and Applied Mathematics, Computer Science, Master 2 at Université Grenoble Alpes
Mathematicien, Mathematics, Engineer, Mathematicien, Mathematics, Engineer at Escuela Colombiana de Ingeniería 'Julio Garavito'
Spanish, French, English, Luxembourgish