"Data scientist" can mean many things, so I like to 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 useful given the situation at hand: I balance using sophisticated, compelling, and new methods with the need for being interpretable, practical, and actionable.
I enjoy developing user-friendly data and analytical software to provide others with the tools they need to store, import, clean, and analyze data in in quick and reproducible ways.
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, data management, 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.