o Co-taught a course on data science tailored to public policy students, using R and Python to explore topics such as data wrangling, version control, reproducible examples, machine learning, and text analysis

o Guided students in collecting real-world datasets, designing models, and conducting analyses to determine and articulate policy proposals

o Oversaw the development of machine learning models to evaluate and propose solutions for topics such as improving the efficiency of the New York City public transit system

o Collected and analyzed publication and citation data on major political science departments to evaluate the university’s relative academic performance

o Built a multi-decade dataset and evaluated the university’s Ph.D. retention rate as well as the success rate of individual faculty members

o Collaborated with faculty on the collection and analysis of datasets to support research, data visualization, academic writing, and statistical modeling using R, STATA, and ArcGIS

o Managed the data collection process — including overseeing an undergraduate researcher — for a precinct-level primary election project, gathering data from 14 states and creating data visualizations to articulate findings

o Designed course materials, planned lessons, provided constructive feedback to students, and led sections in a range of courses, such as American Government and Politics, Introduction to GIS for Social Science Research, and Advanced Statistical Methods for Social Science

o Developed a remote lab process to increase access and efficiency for students and faculty using ArcGIS

o Created dummy and real datasets to demonstrate complex models and mapping processes in R, STATA, and ArcGIS