Rachel Levanger is a data science leader with 11 years of experience who has led Fidelity National Financial’s Data Science practice since 2018, driving DataOps adoption and breaking down information silos to embed data-driven decision making across the enterprise. She pairs a rigorous academic background—a PhD in Mathematics and postdoctoral research at UPenn under Prof. Robert Ghrist—with practical product and systems experience, translating advances in computational topology and persistent homology into applied insights. Her research on topological data analysis and applied sheaf theory informs novel approaches to high-dimensional pattern discovery, particularly in fluid dynamics and complex simulations. Known for bridging theoretical guarantees (e.g., error bounds for persistence diagrams) with business impact, she blends deep math, statistical modeling, and engineering pragmatism to build reproducible analytics at scale. Based in New York, she brings a rare combination of academic rigor and enterprise delivery that surfaces subtle structure in messy real-world data.
11 years of coding experience
1 year of employment as a software developer
Mathematics, Mathematics at Portland State University
BA Mathematics Art History, BA Mathematics Art History at University of North Florida
Doctor of Philosophy - PhD Mathematics, Doctor of Philosophy - PhD Mathematics at Rutgers University
Contributions:97 pushes, 5 branches in 4 years 9 months
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