Summary
James Schmidt is a data analyst with a decade of professional experience and a strong focus on energy and power systems analytics. Currently a Data Analyst III at Danovo Energy Solutions, he leverages Python, SQL, SAS, and R to build ML-driven solutions that inform operational decisions across utilities. His background includes deploying neural networks in Azure Form Recognizer, using satellite imagery for vegetation detection around substations, and developing Django/Postgres optimization tools for project prioritization. Trained in advanced neural network methods and SAS Base certified, he blends rigorous statistical training from NC State with practical cloud and production deployment experience. James’s early work in accounting and lab roles gives him an uncommon operational perspective that helps translate technical models into business value. Based in the Raleigh-Durham area, he excels at turning messy grid and image data into actionable insights for the energy sector.
10 years of coding experience
3 years of employment as a software developer
Bachelor's degree, Statistics, Bachelor's degree, Statistics at North Carolina State University
Business Analytics Honors Program, Business Analytics Honors Program at NC State Poole College of Management