Nathan Tindall

Nathan Tindall is an accomplished economist with a background in econometrics and machine learning, currently serving as a data scientist at Plaid. He is enthusiastic about developing products that incorporate economic modeling, optimization, and prediction.

Before joining Plaid, Nathan gained valuable experience working on pricing algorithms at Uber. He holds a Ph.D. in Economics from Wisconsin-Madison, where his research concentrated on industrial organization and applied microeconomics. During his graduate studies, Nathan specialized in creating innovative empirical methods for analyzing dynamic contribution behaviors, notably in the context of crowdfunding markets.

Nathan Tindall's educational journey includes studying at Wiregrass Ranch High School for his high school education, achieving a Master's Degree in Computer Science from Stanford University, and obtaining a Bachelor's Degree in Symbolic Systems with Distinction, also from Stanford University.

Throughout his career, Nathan has held various positions including Software Engineer at Plaid, Software Engineer Intern at Blend Labs, and teaching roles at Stanford University. He has also worked as a Software Engineer Intern at SalesforceIQ, Kitchen Manager at Stanford University, Research Assistant at Stanford University, and Spark Research Intern in Drug Discovery at Moffitt Cancer Center.