ENSAE Paris - École d'ingénieurs pour l'économie, la data science, la finance et l'actuariat

Award ceremony of the Business Data Challenge 2022-2023 with Meilleurtaux and DataStorm

25 Apr. 2023
Each year, ENSAE Paris organizes the Business Data Challenge: a company proposes, in collaboration with the school's teacher-researchers, an economic or financial topic and provides the data on which several groups of students work for a full semester.
Award ceremony of the Business Data Challenge 2022-2023 with Meilleurtaux and DataStorm

Meilleurtaux renews its partnership as a sponsor of the 2022-2023 edition of the Business Data Challenge! Benoît Rouppert, Chief Data Scientist of Meilleurtaux, came on Tuesday December 6th to present to the students the subject of this 2022-2023 edition of the Business Data Challenge: real estate price estimation. Five teams of 3rd year students from the engineering cycle of the Data Science and Business Decision track, from the Data Science specialized master's degree and from the Quantitative Methods for Economic Decisions specialized master's degree took up the challenge this year, won by team 2 composed of Louise Bonhomme, Michel Daher Mansour, Antonin Falher, Blanche Lalouette and Clotilde Nietge. Congratulations to all of them for the work accomplished during this competition and especially to the winning team!

The students had four months to respond to the submitted problem. The final production consists of a 20-page thesis in English, the rendering of documented computer codes, and an oral defense in front of the jury composed of Guillaume Autier, Benoît Rouppert, Cristina Butucea, Philippe Choné, Michael Visser nd Clara Wolf.

Each group is supervised by Philippe Choné, head of the "Data Science & Business Decision" track, and Emilien Macault, coordinator of the economics course, as well as by the school's teacher-researchers (Roxana FernandezAzadeh KhaleghiMichael Visser), Datastorm consultants (Hassan Maissoro, Arij Sifi and Clara Wolf), and a specialist from the sponsoring company (Benoît Rouppert). An innovative learning format, learning by doing and under the angle of open innovation, allowing students to work with real data by applying all their teachings and more particularly in economic analysis, modeling and implementation of data science techniques (econometrics and machine learning).