Debunking the Myths of Mathematical Optimization: The Future of Data-Driven Decision-Making
Mathematical optimization offers its own prescriptive decision-making role to help teams make informed decisions on complex
Jerry Yurchisin is the Data Science Strategist at Gurobi Optimization. He has over a decade of experience in operations research, data science, and visualization, and specializes in enhancing decision-making. Before joining Gurobi, Jerry worked in consulting (OnLocation, Inc. & Booz Allen Hamilton), supporting numerous projects by building and customizing mathematical optimization models and leveraging machine learning, applied statistics, and simulation to support decision-making through data-driven narratives. Jerry also has a background in college-level mathematics instruction and has experience in career management from his time at Booz Allen Hamilton. Now, at Gurobi, Jerry aims to promote the integration of mathematical optimization into the data science and broader AI communities.
Mathematical optimization offers its own prescriptive decision-making role to help teams make informed decisions on complex
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