Jacques Peeters is a lead data scientist at ManoMano, a European home improvement marketplace. His work covers a broad slice of what makes a marketplace run: recommender systems that connect customers with the right products, sales forecasting, bidding algorithms, and customer targeting. Moving between those problems has made him comfortable taking models from experimentation to business impact.

Jacques is also a serious data science competitor, with a record that would stand out on any team. He took 2nd place out of 1,030 participants in the DrivenData Power Laws energy consumption forecasting competition, earning a 7,000 euro prize, and 6th place out of 1,560 teams in the ACM RecSys Challenge 2019 on Trivago’s context-aware recommender system. On Kaggle, he finished 24th out of 900 in the Walmart unit sales uncertainty competition, in the top 1 percent (42nd out of 4,820) in the Elo Merchant Category Recommendation competition, and in the top 2 percent (52nd out of 2,620) in the Instacart Market Basket Analysis competition.

That combination of production data science and elite competition performance means Jacques brings both rigor and speed to the problems he works on.