Summary
Pierre Fay is a Data Analyst and PhD candidate in Finance based in Lille with 11 years of experience bridging senior backend development and quantitative finance research. He transitioned from a long career as a Magento/ PHP technical lead in retail and luxury to data science in 2018, now combining production-grade engineering (Docker, SQL, FastAPI, Dagster) with econometric and ML methods (ARIMA/VAR, GSADF, NN/LSTM). Pierre routinely builds end-to-end pipelines—crawlers/APIs, data quality checks, feature engineering and model backtests—and brings MLOps/DevOps practices (MLflow, Docker, GitHub Actions) into academic research and enterprise retail media projects. He has led international e-commerce platform launches and support teams, giving him rare operational insight into how data-driven models impact commerce flows and logistics. Curious about LLMs and open-source tooling, he experiments with Ollama and other LLM stacks alongside traditional data tooling like DuckDB and Polars. That mix of hands-on platform experience and rigorous finance research helps him turn complex datasets into actionable growth and automation levers.
11 years of coding experience
12 years of employment as a software developer
DUT , Informatique, DUT , Informatique at IUT A, Université de Lille I
Master of Science - MSc, Computer Science, Master of Science - MSc, Computer Science at SUPINFO
Phd, Finance, Phd, Finance at IAE Lille
French, anglais (toeic 850), espagnol (bon niveau)