Jeff is a data analyst with experience in machine learning, management science, and data visualization. He uses tools such as Python, R, SQL, GIS, and Microsoft Power BI to apply advanced analytics and modeling, answer business and policy questions, and generate high-impact dashboards and data visualizations. Skilled in statistical analysis, he uses software such as SAS and Stata to manage large datasets and test for causal effects within policy contexts.
At Insight, Jeff supports projects for the U.S. Department of Education, the U.S. Department of Labor, the U.S. Department of Veterans Affairs, the National Science Foundation, and other clients. His work entails using natural language processing to improve machine learning algorithms classifying text documents, using Python to create automated reports and data visualizations, and using SAS to run statistical tests and analyses on survey data.
Prior to joining Insight, Jeff was a science teacher in two school districts, where he helped develop curriculum and lead professional development for fellow teachers. His students surpassed local and state performance averages on standardized tests. Jeff earned his M.S. in public policy and management with a focus on data analytics from the Heinz College of Information Systems and Public Policy at Carnegie Mellon University.