A PhD Statistician and Data Scientist with over a decade of experience in academia and industry (currently at Stem, Inc., previously at Thrasio and the University of Notre Dame). He specializes in spatiotemporal data modeling, Bayesian analysis, and time series forecasting. His academic research applied statistical methods to atmospheric sciences and greenhouse gas emissions. He is skilled in Python, R, SQL, Spark, and various machine learning techniques, with a strong focus on turning complex data into business value and addressing climate-related challenges.