Stefani is an expert social scientist with extensive academic training and experience managing research teams. She has training in political science, public policy, and computational social and data science. Stefani collaborates with our policy and commercial teams to evaluate and implement data science solutions. Using supervised and unsupervised machine learning methods and data science best practices, she helps generate insights for our government and commercial clients.
Stefani has more than five years of experience collecting, processing, and analyzing data from small to large in scale, using various methodological techniques. These projects range from scraping and parsing legislative and administrative data to developing and synthesizing traditional surveys. Additionally, she has more than five years of experience employing advanced statistical modeling, including Bayesian, generalized linear model, and experimental. She also has three years experience in social media analytics, including natural language processing and text analysis. Stefani has published academic articles using quantitative methods on topics such as legislative policy capacity, the diffusion of environmental policy, and the influence of political indicators on state-level lawmaker behavior.
Her previous roles include researcher/instructor of political science and methodology at the University of Colorado Boulder and data science product developer at Decoded. Stefani is also a postdoctoral researcher in the department of politics at Birkbeck College, University of London.