Nathan Lis

Nathan Lis is an experienced Meteorological Data Scientist at DTN since August 2020, where significant contributions include the development of the Storm Impact Analytics machine learning model to enhance predictions of weather-related power outages. Prior experience as a Graduate Research Assistant at the Cooperative Institute for Severe and High-Impact Weather Research & Operations involved creating operational icing detection products for the FAA and improving hydrometeor classification algorithms. Nathan co-founded Innovation Weather, LLC, focusing on developing algorithms for weather risk mitigation and customizing weather models for agriculture and commodities trading. Academic credentials include a Master of Science in Meteorology from the University of Oklahoma and a Bachelor of Science in Atmospheric Sciences and Meteorology with dual minors in Geographic Information Science and Piano Performance from Penn State University.