Summary
Thomas Pernet is a Data Scientist and academic researcher with a PhD in Economics and eight years’ experience applying machine learning and econometrics across marketing, finance, insurance, and e‑commerce for clients on every continent. He blends rigorous academic research—publishing on environmental economics and climate risk—with hands‑on engineering, having built production-grade LLM-assisted analytics, orchestration DAGs, and end-to-end NLP systems in finance. Notable projects include an auditable SQL-to-LLM orchestration engine for asset managers, large-scale company tagging with fine-tuned LLMs, and predictive models that cut payment delays and boosted investor–company matchmaking. Comfortable across cloud architectures (AWS, BigQuery, Vertex AI), graph ML and Neo4j, he excels at turning complex economic questions into transparent, deployable data products. Based in Paris, he’s seeking roles that fuse applied economics, NLP and AI to drive impactful solutions in the finance industry—often taking a domain-driven, production-first approach that avoids one-size-fits-all tooling.
8 years of coding experience
7 years of employment as a software developer
Master's degree, International Economics, high honour, Master's degree, International Economics, high honour at Université Panthéon Sorbonne (Paris I)
Linguistic program, Chinese, Linguistic program, Chinese at 北京经济管理职业学院 Beijing Institute of Economics Management
Institut Confucius Paris Diderot
Doctor of Philosophy - PhD, International Economics, Doctor of Philosophy - PhD, International Economics at University of Paris I: Panthéon-Sorbonne
Master’s Degree, International trade, high honour, Master’s Degree, International trade, high honour at Ecole normale supérieure
PhD of Economics 博士, Economics, PhD of Economics 博士, Economics at Fudan University
English, Chinese