Christopher Burke

Senior Data Scientist - AI Modeler at FiscalNote

Christopher Burke is a seasoned data scientist with extensive experience in risk modeling and AI methodologies. Currently serving as a Senior Data Scientist - AI Modeler at FiscalNote since January 2024, Burke previously worked at At-Bay, where responsibilities included developing an in-house cyber catastrophe model and implementing loss calculation in Python and SQL. As Principal Scientist at Karen Clark & Company, Burke built catastrophe models for natural disasters using a mix of machine learning, statistical, and physical simulation methods. Prior roles include Postdoctoral Researcher at the University of Massachusetts Amherst, focusing on polymer nanostructures, and Graduate Research Assistant at Tufts University, where simulations for molecular configurations were developed. Christopher Burke holds a Ph.D. in Soft Matter Physics from Tufts University and a Bachelor’s Degree in Physics from Lehigh University.

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FiscalNote

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FiscalNote is the premier information services company focused on global policy and market intelligence. By combining AI technology, expert analysis, and legislative, regulatory, and geopolitical data, FiscalNote is reinventing the way that organizations minimize risk and capitalize on opportunity.