Claire McKay Bowen
Lead Data Scientist, Privacy and Data Security, Urban Institute

Educational Background
MS and PhD, Statistics, University of Notre Dame
BS, Mathematics and Physics, Idaho State University

Raised on a small farm in Idaho, Claire McKay Bowen’s family encouraged her to explore and question the world around her. They fueled her curiosity by taking camping trips, reading books in the library, hiking and skiing the Rockies, and building and destroying a few projects on the farm. In particular, the women of her family showed her she could become anything she wanted to be, even though society had a different perspective, especially living in rural Idaho. However, from her family’s support, she was already determined to become a scientist.

From her desire to understand how the world worked, McKay Bowen pursued a degree in mathematics and physics at Idaho State University. Her undergraduate studies affirmed her love of science and mathematics and solidified her decision to become a researcher. She participated in a variety of internship programs at other universities such as physics education at the University of Washington and biophysics at the University of Illinois at Urbana-Champaign. Throughout these experiences, McKay Bowen realized (with the help of her spouse) what intrigued her most in the research projects was the statistical analysis and how it was applied to solve real-world problems. She then decided to pursue a doctorate in statistics at the University of Notre Dame, where her dissertation topic was Data Privacy via Integration of Differential Privacy and Data Synthesis. She received the Microsoft Women’s Graduate Research Fellowship, National Science Foundation Graduate Research Fellowship, and Gertrude M. Cox Women’s Scholarship during her graduate career.

After her graduate career, McKay Bowen became a postdoctoral research associate in the Statistical Sciences Group at Los Alamos National Laboratory (LANL). She developed functional data analysis techniques for iterative design problems, investigated cosmic ray effects on supercomputers, and continued data privacy research on metric evaluations of differentially private synthetic data. As a postdoc, she was nominated for the inaugural Rising Stars in Computational and Data Sciences Workshop.

McKay Bowen is now the lead data scientist for privacy and data security at the Urban Institute. Specifically, she is working on a team to create synthetic data on a variety of data sets (e.g., income tax return data), assess the quality and privacy guarantees of the generated synthetic data, and develop methods for researchers to safely and securely access more confidential data.

Outside of research, McKay Bowen’s greatest accomplishment is completing a full Ironman (2.4-mile swim, 112-mile bike, and 26.2-mile run). She is also an active knitter, snowboarder, and hiker.