- Developed second version of an assortment optimization algorithm for retailers. Based on k-means clustering algorithm and optimization under constraints, it aims to define the best products assortment for a given store and product category, leading to a 7% sales uplift in average.- Conducted research and proof of concept of a Next Best Offer algorithm, which aims to define the best products recommendations for a given group of client. Used a hybrid method between collaborative filtering and content-based.

Data scientist within Machine Learning & Analytics team. Empowered Richemont luxury maisons with data insights, driving strategic decision-making.- Conducted technical aspects of Media Mix Modeling for 3 luxury brands within the group, quantifying advertising channel impact through statistical analysis and giving precious insights to marketing teams.- These results allowed the data-driven optimization of marketing strategies to maximize ROI and sales. Led to a significant estimated sales uplifts of 10%, 14%, and 14.8% for targeted brands.- Developed custom objective functions within MMM optimization to prioritize specific business goals (e.g., maximizing sales with a given budget, minimize the budget needed to reach a turnover target)

Led the prototyping of a connected bracelet, conducted client prospecting, and performed market research.

BEST CentraleSupelec is a student association of CentraleSupelec and a founding member of BEST (Board of European Students of Technology), which encourages communication, cooperation and exchanges between a hundred engineering schools across 34 countries in Europe. As a General Secretary (1 of the 4 members of the board) I was in charge of: Statute management, scheduling and reporting, organization of general meetings.