Lily Fesler is a Senior Researcher at Mathematica. She specializes in causal inference (experimental and quasi-experimental methods) and natural language processing (NLP) methods. She directs projects for the National Science Foundation and the Gates Foundation, and is the principal investigator on a project for the Overdeck Family Foundation. She leads teams of data scientists, economists, and qualitative researchers to carry out complex, multi-year studies. She also leads study design and reporting for diverse audiences for multiple projects.

She received her PhD in economics of education from the Stanford Graduate School of Education in 2020, where she was a NAEd/Spencer Dissertation Fellow, an Institute of Education Sciences Fellow, and a Stanford Graduate Fellow in Science and Engineering. Her dissertation research used text-as-data, machine learning, and synthetic control methods to characterize students experiences navigating the transition from high school to college. She served as a teaching assistant for courses on applied quasi-experimental methods in education and founded the group Computational Text Analysis in the Social Sciences (CTASS) at Stanford. She received her MA in economics at Stanford and her BA in economics from Wesleyan University.

​She previously interned with the policy research team at the College Board,  worked as an education analyst at Abt Associates and as an economic analyst at Compass Lexecon.