Zachary R. McCaw

Ph.D. in Biostatistics, Harvard

Experience

Zachary McCaw is a machine learning scientist and biostatistician. His research focuses on making scientific discovery more reliable and interpretable through new statistical and machine-learning methods. He has co-authored 70+ scientific publications, is a co-inventor on three granted U.S. patents, and has developed multiple statistical methods and open-source R packages.

  • Causal Labs, 2026–present — Member of Technical Staff: Developing learned world models to support planning and policy learning.
  • Voleon, 2025–2026 — Senior Member of Research Staff: Researched transformer architectures and self-supervised representations for financial forecasting.
  • Insitro, 2021–2025 — Staff Machine Learning Scientist: Developed phenotypic representations for genetic discovery, risk stratification, and treatment response prediction.
  • Google, 2019–2021 — Data Scientist: Developed methods for genetic discovery from machine-learning-derived phenotypes, and for causal inference on developer productivity.

Education

  • Stanford University, 2021–2022: Graduate Certificate in Artificial Intelligence.
  • Broad Institute, 2019: Visiting Scientist with Professor Hilary Finucane.
  • Harvard University, 2014–2019: Ph.D. and A.M. in Biostatistics under Professor Xihong Lin.
  • National Institute of Environmental Health Sciences, 2010–2014: Research Fellow with Professor Steven Kleeberger.
  • UNC–Chapel Hill, 2009–2013: B.S.P.H. in Biostatistics and B.S. in Quantitative Biology.