Kiersten joined the EAB Data Science team in 2018, directly after graduating from university. She maintains the Student Success Predictive Model and helps develop new data-science-driven tools for managing student retention, graduation, course load, and major switching. She specializes in research—answering institution-specific questions, exploring new data sources for informative patterns, and finding novel ways to connect different facets of student life in order to better inform student support resources.
Outside of work life, Kiersten loves to cook and bake, finding great joy in presenting her friends with a colorful bowl of udon noodles or a fragrant batch of tea cookies. She also is an avid weightlifter and dedicates her evenings to balancing out the consequences of her love for food.
Kiersten graduated from Carnegie Mellon University in Pittsburgh, PA with a Bachelor of Science with University Honors in Statistics and an additional degree in French and Francophone Studies.