In a time where "data scientist" can mean many things, I like to get a bit more specific and say that I am a quantitative social scientist. I use statistical and machine learning approaches to solve problems and answer questions concerning areas like attitudes and behavior. I see my role as being the bridge between (a) the technical and academic world, and (b) stakeholders that could benefit from the knowledge generated by that world.

I love using quantitative methods to provide clients with actionable insights, while still remaining skeptical and communicating the uncertainty inherent in quantitative methods. My approach appreciates the tension between what a journal article recommends we do in a perfect world and what is possible given the messiness of real data from the actual world: I balance using sophisticated, compelling, and new methods with the need for being interpretable, practical, and actionable. I also enjoy developing user-friendly analytical software with this approach in mind to provide others with the tools they need to accomplish their goals.

I have a Ph.D from the University of Kansas in social psychology, with a minor in the study of quantitative methods. I also have B.A.s in psychology and sociology from the University of Missouri. I am passionate about combining my skills in a wide variety of statistical methods, programming, machine learning, experimental design, causal inference, and survey construction with domain expertise in the psychology of norms, attitudes, behavior, and politics to help promote progressive values and social good.