Andrés Nigenda

Andrés Nigenda is a lead data scientist at Mathematica who works at the intersection of artificial intelligence (AI), complex administrative data, and policy decision making. Andrés’ work focuses on helping federal agencies modernize how they collect, analyze, and use data to generate evidence that supports science, education, and workforce policy.

At Mathematica, Andrés oversees multidisciplinary technical teams and ensures that data science and engineering approaches are aligned with policy goals, governance requirements, and operational constraints across end-to-end data pipelines and analytic systems. He has served as a project director and deputy project director on projects for the National Science Foundation (NSF) and the Centers for Disease Control and Prevention. Andrés has held technical leadership roles on evaluations examining program outcomes, grantmaking processes, and policy pilots, applying natural language processing and causal inference methods to complex administrative and text data for clients such as NSF and the U.S. Department of Labor. For the National Center for Science and Engineering Statistics (NCSES), he has led and contributed to the development of analytic capabilities and tools that enable federal agencies to track how their data assets are used in scientific publications, supporting ongoing monitoring, reporting, and decision making.

Before joining Mathematica, Andrés worked in the Mexican federal government on impact evaluations and data-driven reforms in health and social policy. He holds an MS in Computational Analysis and Public Policy from the University of Chicago. Andrés is motivated by advancing transparent and trustworthy data systems that help public institutions better understand program outcomes and strengthen evidence-based policymaking.