Deciding on the best place to build a new bike-sharing station in New York City based on ridership data landed a team of Berkeley Master of Financial Engineering students first place in the Citadel West Coast Datathon. The competition was held at the San Francisco Marriott Hotel on January 25.
Team members: Raymond Ji, MFE 20, Yili Wang, MFE 20, and Weipeng Shao, MFE 20, working with Ying Jin, PhD 24 (statistics), of Stanford University.
The Field: Twenty-three teams from top U.S. universities on the West Coast, including Caltech, Stanford, UCLA, University of Southern California, and the University of Washington, competed for $20,000 in prize money and the chance to move on to the Citadel National Data Championship in April.
The Challenge and Team’s Plan: The team had to decide where to build a bike-sharing station in New York City based on current and future ridership, demographics, proximity of public transportation, and the popularity of ride-sharing alternatives. Using those data points, the team built a regression model that accurately predicted South Brooklyn as the best location for a bike-sharing station.
The Secret Sauce: “Our wide skill set as well as our extensive preparation set us apart from the other teams,” said Raymond Ji, MFE 20. “Our ability to dig well in depth into a topic question while still covering a broad range of aspects and techniques helped us win the competition.”
The Haas Factor: The students said Prof. Martin Lettau’s Empirical Method in Finance course and Prof. Laurent El Ghaoui’s Finance Data Science course provided useful knowledge for the competition.