Data scientist and computational social scientist with over a decade of experience introducing and institutionalizing new data science capabilities at some of the world’s top social research and political advocacy organizations.
As the lead data scientist at WorkMoney, I’m currently leading the charge on figuring out who our millions of members are, and how we can best help them. In my previous roles as the senior data scientist at Pew Research Center’s Data Labs, and an inaugural data scientist at the National Opinion Research Center (NORC), I managed and executed a wide range of data-intensive social science research projects that required close collaboration with research, stats and tech experts to define research goals and design, develop, and deliver products involving natural language processing, machine learning, data systems engineering, and large-scale data collection.
My research portfolio has covered a wide variety of interdisciplinary challenges, including measuring and tracking U.S. political trends, quantifying the “meaning of life,” conducting online surveillance of human trafficking activities, building a map of YouTube, detecting emerging trends in substance abuse, analyzing HIV risk in local community networks, measuring strategic adaptation across international terrorist organizations, quantifying parent engagement in early childhood education, standardizing unstructured criminal records, and parsing medical information from high volume healthcare records.
My work has been covered by the New York Times, the Washington Post, and many other prominent national and international publications, and I regularly present at a variety of academic and industry conferences including AAPOR, ASPA, and IC2S2.