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Nathan has a background in physics, and brings machine learning and data science experience to the team.

His academic research was based at the CERN Large Hadron Collider, where he developed new ways to mine petabyte-scale datasets for insights about the smallest building blocks of matter.

More recently, Nathan was a Lead Data Scientist at Macy’s, where he developed and deployed models, designed measurements, and provided analytics to support a variety of use cases in marketing.

Nathan holds a B.S. in Physics and Mathematics from the University of Minnesota, and an M.S. and Ph.D. in Physics from Cornell University.