Scott comes to CIPHR with prior research experience in analytical chemistry as a Research Associate at the University of Southern Maine’s Quality Control Collaboratory, where he focused on High-Performance Liquid Chromatography method development. During his graduate studies, Scott shifted his focus to public health research, applying machine learning and statistical techniques to health data.

His Master’s capstone project involved using Hospital Readmission Reduction Program (HRRP) data to develop a Random Forest model to identify key risk factors associated with hospital readmission following hip and knee replacement surgery. These factors were then used in Elastic Net and Support Vector Machine models to predict hospital readmission rates and to classify hospitals as ‘preferred’ or ‘non-preferred’ based on national readmission performance benchmarks.

In addition to his research background, Scott has previous clinical experience working as a Primary Care Medical Scribe with Maine Medical Partners and as a Perioperative Technician at Maine Medical Center. He also has experience in biotechnology, contributing to the development and manufacture of rapid diagnostic products.