Internship Location: Madison WI
Organization Type: Nonprofit
Policy Areas: Data Science in policy
During my internship, I gained a much better understanding of what data science work can look like in a policy setting. I worked closely with administrative data, which gave me insight into various social safety net programs. This experience expanded my knowledge of policy design and implementation and emphasized the importance of data-driven decision-making in addressing real-world challenges. During the first part of my internship, I worked on trying to gather as much data as I could on social welfare programs that would be relevant for researchers to have on hand when starting a project. The second part of the internship was finding a way to display this data in an accessible way. I decided to use Python to create data frames to display the information I had gathered about different programs so they were easily searchable. The most valuable part of my internship was the opportunity to apply my classroom learning in a practical context. Additionally, working with a supportive and knowledgeable mentor significantly improved my skills, as I received frequent feedback that helped me tackle challenges more effectively. I would highly recommend this internship to future students, especially those interested in the intersection of data science and policy. It offers a unique opportunity to work with real-world administrative data, apply technical skills, and learn about the complexities of policy-making in practice. This experience has confirmed my interest in pursuing roles that combine data science with policy analysis, and given me an example of a tangible way my skills can contribute to meaningful societal outcomes.