I just finished a PhD in math and advanced data science at the University of Washington, and I run @wnbadata, where I make short video explainers about women's basketball data and analytics.
I'm looking for data science work in basketball, especially women's basketball. Most of what I do is play by play analysis in R, and then figuring out how to convey the analysis in 45 seconds with a story and charts.
- wnba-analysis — curated projects, written up properly. Ridge regression on team stats, PageRank rankings, DPOY prediction.
- wnbadata — the working archive. 180+ scripts since 2024, one per video, including the weirdest stat about every WNBA team, 15 videos in 16 days.
- Data intern at Sports Reference, writing SQL against historical basketball data
- Women in Sports Data Fellow with Philadelphia Phillies R&D
- Mentee at the MIT Sloan Sports Analytics Conference
- Paid content partner with the WNBA, explaining their AWS-powered shot quality metric to fans
- Created and taught Math 380: Communicating Mathematics Through Sports Data at UW, as instructor of record
R, Python, SQL. Bayesian inference, regression, clustering, and a lot of ggplot2.