I'm a data scientist who works on the business side too: I build forecasting, pricing and simulation models, and I scope, price and run the engagements around them, on site with the teams who use them.
Now
Consultant to Groupe Etam (Etam, Undiz, Maison 123), October to December 2026. On site with the Data & AI team, I run the demand-forecasting and promotional-pricing models behind year-end markdowns and winter sales. I scoped and priced the 57-day, €28,500 engagement; it was accepted seven days after I met the group's Director of Data & AI.
Previously
- SmartFleetOptim, founder and lead engineer (co-founded in April 2026, sole founder from June to September). A Monte Carlo stress test that tells an airline which spare aircraft pay for themselves. I built it end to end, took it to airlines myself and demoed it to the operations-control teams of SWISS and Finnair. No pilot or sale resulted.
- Air France Network, data analyst intern, October 2024 to March 2025. Built the Python decision tool and Power BI dashboard that Network management used to allocate spare aircraft across long- and medium-haul.
Engineer from Télécom SudParis, with a double degree in data science from Télécom Paris (IP Paris). 2nd overall at the Airbus × IBM × AWS hackathon. Small fixes merged in POT, pytorch-grad-cam, prince and gradio.
Methods I use: probabilistic forecasting (quantile gradient boosting, conformal intervals), Monte Carlo simulation, linear programming and model predictive control, in Python and SQL. The pinned case studies below each answer one business question and say so when the simple baseline wins.
Moving to New York in January 2027 for a solutions, forward-deployed or business-development engineering role. pierrechambet@gmail.com · LinkedIn