Prior to joining the Center, David has focused on the impacts of social assistance policy innovations in local Brazilian government, using mixed methods research design. This involved cleaning, validating, and assessing the dimensionality of data from panel surveys that measured policy attributes in 5,570 Brazilian municipalities, as well as semi-structured interviews with key state actors and stakeholders in civil society. He has experience generating useful insights from complex, observational data in a range of settings. Recent projects include: the automated coding of 150,000 transcribed statements by legislators to identify the salience of subject matter form a custom dictionary of terms; using quasi-experimental methods, such as matching and difference-in-differences, to identify the short- and medium-term economic shocks to local economies following an unexpected mass migration event in Brazil; and modeling the workplace network density of public sector employees to test whether differing network structures are associated with greater job satisfaction.

David received a BA in English from Louisiana State University in 2007 and a master’s in Latin American Studies from Tulane University in 2013. He received a master’s degree in political science in 2017 from the University of Pittsburgh, where he is currently ABD in his PhD studies in political science. He has also worked as an educator in various settings: as an English teacher in Spain, Nicaragua and Brazil; a high school Spanish teacher; an adjunct professor of Spanish and Portuguese; and an instructor of undergraduate political science courses.