Sep 23–26, 2019

Josh Hamilton
Data Scientist, Major League Baseball

Josh Hamilton is a data scientist at Major League Baseball, where he works with the league and its 30 teams to build data pipelines and predictive models. Previously, Josh helped build data infrastructure and recommender systems for a movie streaming company and worked as a product manager for a platform-as-a-service startup. He studied finance and economics and holds an MS in applied statistics from the University of Alabama.

Sessions

5:25pm–6:05pm Wednesday, September 25, 2019

Location: 1A 08/10

Data science and the business of Major League Baseball

Data Science, Machine Learning, & AI

Secondary topics: Media and Advertising

Aaron Owen (Major League Baseball), Matthew Horton (Major League Baseball), Josh Hamilton (Major League Baseball)

Using SAS, Python, and AWS SageMaker, Major League Baseball's (MLB's) data science team outlines how it predicts ticket purchasers’ likelihood to purchase again, evaluates prospective season schedules, estimates customer lifetime value, optimizes promotion schedules, quantifies the strength of fan avidity, and monitors the health of monthly subscriptions to its game-streaming service. Read more.