Curtis McGinity is a skilled consultant with experience in data science, machine learning, data modeling, and dashboard design, as well as technical writing and direct client communications. He brings an advanced technical skillset to deliver data-driven insights to clients.
Curtis joined Emergent Method in 2021 after serving as a senior consultant for Emergent Talent, a division of the firm. There, he designed and developed an enterprise data model and machine learning pipeline for operational performance monitoring, created analytic dashboards for technical teams and the C-suite, and managed data warehouse and master data management operations. Before working with Emergent Method, he served as Professor of Management Science and Information Systems at Rutgers Business School and as a research associate for the CCI Center for Advanced Data Analysis.
Curtis earned his doctorate in Operations Research from Rutgers University for his work on dynamic risk in reinforcement learning models. He holds a Bachelor of Science in Mathematics, Physics, and Economics from Tulane University.