Carrie Grimes Bostock graduated from Harvard with an A.B. in Anthropology/Archaeology in 1998, and an interest in quantitative methods for dealing with disparate data. She graduated from Stanford in 2003 with a PhD in Statistics after working with David Donoho on Nonlinear Dimensionality Reduction problems, and has been at Google since mid-2003.

Dr. Grimes Bostock spent many years leading a research and technical team in Search at Google trying to figure out what criteria make a search engine index "good," "fast," and "comprehensive" – and how to achieve those goals, before working in Technical Infrastructure at Google as a Technical lead for Fleet performance, deployment and optimization. Currently, she is working on enabling more innovative machine learning at scale for Google products and beyond.