Margrét Bjarnadóttir specializes in operations research methods using large scale data; her research centers around data-driven decision making, combining optimization modeling with data analytics. Her work spans applications in health care, finance, people analytics and sports. In healthcare she specializes in decision modeling using EMR and claims data. A recent paper, “Aiding the Prescriber,” focuses on risk modeling for improved opioid prescriptions. Another, “Predicting Colorectal Cancer Mortality,” uses EMR and Cancer Registry data to build decision support tools. Examples of other applications include drug surveillance design, practice patterns and patient targeting. The focus of her People Analytics work is on algorithmic studies of demographic pay-gaps, including the best approaches to remedy the pay-gap problem taking into account both equity and the economics. In her recent paper “On a Firm's Optimal Response to Pressure for Gender Pay Equity” she highlights some of the unintended consequences of pay-gap legislation. In finance, she studies complex networks, including analysis of cross-ownership patterns and systemic risk. More recently she and her co-authors are studying the complex financial supply chains behind financial products. She has consulted with healthcare start-ups on risk modeling and with governmental agencies on data-driven fraud detection algorithms.