Summary
Rick Russotto is a Senior Data Scientist and climate scientist with a decade of experience translating atmospheric research into production-ready Python tools and risk products. He has led development of global machine-learning indices and a tropical cyclone return-period model at Gro Intelligence, and now builds weather-risk products for wildfires and flash floods at DTN. His work bridges high-end climate modeling (characterizing hurricanes in NASA GISS Model E3) and pragmatic engineering—rewriting legacy Matlab/Fortran analyses into unit-tested, gridded Python pipelines for interoperable datasets. Rick combines strong academic credentials (PhD/MS, UW; summa cum laude BS, Yale) with hands-on catastrophe modeling and ensemble climate projection work, and he has a habit of turning complex scientific methods into scalable, operational code.
11 years of coding experience
15 years of employment as a software developer
M.S., Ph.D., Atmospheric Sciences, 3.87/4.00, M.S., Ph.D., Atmospheric Sciences, 3.87/4.00 at University of Washington
B.S., Summa Cum Laude, Geology and Geophysics, 3.96/4.00, B.S., Summa Cum Laude, Geology and Geophysics, 3.96/4.00 at Yale University
International Baccalaureate Diploma, International Baccalaureate Diploma at Deerfield Beach High School