In the summer of 2017, I worked as a Business Analytics and Data Science Intern in the Venue Services department at the New York Mets.
Simply, this was a dream come true and one of the coolest experiences of my life. It was amazing to work on analytics problems with the team that I had long been a fan of. While I was the only data analyst on the team, at the time, it was really useful to exposed to all the data that they had and use it in interesting ways.
In this role, I examined and developed various reporting measures to explore the daily food, beverage, merchandise and memorabilia sales in order to make recommendations and improvements to the in-stadium operations. In this position, I was able to create my own metrics, which used by the team to understand a wide array of tasks ranging from what retail items should be offered at discount prices, based on projected future sales, to what food stands were underperforming.
Using Python and various proprietary raw data feeds, I was also tasked with creating various reports and visualizations to relay information to the team’s Vice President of Venue Services and Director of Merchandise, to help elucidatetrends in our daily, weekly, monthly and yearly operations. Through such analysis, I was able to make dozens of implementable recommendations that altered the team’s strategy for ordering apparel, targeting returning memorabilia buyers, making data-centric improvements to the fan experience, among many other things. As an example of my success with the team, one of my recommendations played an instrumental role in doubling our year-to-year concert revenues.