Summary
Matt Pettis is a seasoned data scientist with more than 12 years of experience spanning manufacturing, retail, and IT, currently applying his craft as a Senior Data Scientist at Trane and a Principal Data Scientist at Honeywell. He combines deep expertise in machine learning, time series forecasting (ARIMA), and data engineering with hands-on production deployment using Docker, Flask, Plumber (R), and OpenAPI to deliver end-to-end ML solutions. Proficient in Python, R, SQL, and Bash, he has built and operationalized models through RESTful endpoints integrated into production pipelines. His leadership experience includes guiding data science teams as a senior/principal data scientist, along with a rich history of roles from lead systems engineer to contractor, and even teaching 8th grade, reflecting a versatile communicator and problem-solver. Based in Minneapolis, MN, he holds a BA in Mathematics and Physics from Gustavus Adolphus College and an MS in Mathematics and Environmental Engineering from Northwestern, underscoring a strong quantitative foundation. He has applied models to manufacturing processes as well as economic and retail domains, bringing a practical, production-focused approach to advanced analytics.
12 years of coding experience
27 years of employment as a software developer
MS, Mathematics, Environmental Engineering, MS, Mathematics, Environmental Engineering at Northwestern University
BA, Mathematics, Physics, BA, Mathematics, Physics at Gustavus Adolphus College