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Prediction of flight delays for a European airline
Alexandre Jacquillat, email@example.com
Flight delays have historically been one of the main drivers of airlines’ operating costs and air traffic inefficiencies. In the future post-COVID world, airlines will need to re-design networks and schedules of flights, offering an opportunity to keep delays at minimal levels. In this project, we partner with a European airline to predict flight delays, as a function of temporal factors (time of day, season), spatial factors (departure, origin), volume of flights, weather information, number of passengers, etc. You will be implementing machine learning models in Python, in collaboration with a Master of Business Analytics student. The full team will meet once or twice per week; during these meetings, you will be reporting progress on data processing, modeling and results. Please email your resume and a short description of your interest and relevant experience to Alex Jacquillat (firstname.lastname@example.org) and Gabrielle Rappaport, Master of Business Analytics (email@example.com).
Experience with Python, and knowledge of machine learning methods.