Shawn Simpson

Education
PhD, MA, Statistics, Columbia University
BS, Electrical Engineering, University of Illinois

Shawn Simpson grew up in Champaign, Illinois, and feels fortunate to have had teachers and parents who recognized her love of math and kept her challenged. She went to University High School, which had a small, funky student body and a strong math curriculum.

Since Simpson liked math and computers and thought soldering extra chips into her PlayStation was cool, she decided to major in electrical engineering at the University of Illinois at Urbana-Champaign. It wasn’t until she did undergraduate research analyzing LIDAR data that it became clear how powerful statistics was as a field; she sees navigating uncertainty and uncovering data signals as having many wonderful applications. Following that, Simpson pivoted to statistics and ultimately earned her PhD in statistics from Columbia University. Her adviser, David Madigan, worked on big data problems and had a practical, computational approach that Simpson thinks was excellent preparation for being a data scientist.

Simpson was an assistant professor at Columbia for a few years before transitioning to industry as data science began to be its own specialty. Her first role was at Dow Jones, where she ran multivariate experiments on WSJ.com and learned a lot about managing cross-functional groups. At Tapad, an ad-tech startup, Simpson gained experience in modern big data tools such as Scala/Spark and worked closely with engineers. Currently, she is a director and principal data scientist on the AI Labs team at BlackRock in New York, where she leads a group that builds tools for traders powered by statistics and machine learning. They also collaborate with Stanford faculty in statistics (Trevor Hastie and Rob Tibshirani), which gives her a bit of an academic connection again.

Simpson’s proudest moments have been defending her PhD; finishing a half-marathon; and giving birth to her son, Byron. Also, a few of her papers from graduate school about drug safety have been cited by COVID-19 research, which was exciting for her to see. Outside work (and pandemic times), she enjoys running, swimming, painting, salsa dancing, and exploring NYC. Her advice to young statisticians is to reach out to others for support and seek feedback early and often. “No one can do this alone,” she says.