👋 About Thomas Francois

I’m a French-born Lead Data Scientist at Lyft with a background in engineering and mathematics. After graduating from Arts et Métiers ParisTech and earning my master’s in Supply Chain Engineering from Georgia Tech, I’ve spent the past several years working across the full data spectrum—from dashboards and data pipelines to experimentation, advanced causal analysis, machine learning, LLMs, and AI agents.

My career began at The Home Depot (2018–2021) as a BI Engineer, where I developed data pipelines, dashboards, and analytics tools for supply chain optimization. Seeking deeper work in data science and experimentation, I joined Lyft at the end of 2021. I first worked on the AV team before moving to Lyft Business, where I progressed through junior, senior, and lead roles. This is where I focused on experimentation, machine learning, advanced causal analysis, and AI agents.

I learned through both formal education and self-study—countless nights of tutorials and books on ML, DL, and now LLMs. I specialize in applying these technologies to real-world industries like transportation, supply chain, and real estate.

Outside of work, I build AI tools that merge data strategy, automation, and user experience— from real estate valuation agents to AI resume copilots. My goal is simple: make AI useful, usable, and measurable for every business.