On April 6, the Economics Department’s Master of Science in Quantitative Economics (MSQE) program hosted a panel for current and prospective students interested in careers in the AI industry. The event offered students an opportunity to learn more about the program and the kinds of professional paths it can open.
Panelists emphasized that the MSQE program provides rigorous training in quantitative skills such as Python, data analysis, and econometrics. Just as important, however, is the program’s grounding in economic theory and its application to real-world problems. The speakers noted that one of the most valuable skills students develop is the ability to frame a problem clearly and design thoughtful solutions.
The panel also highlighted that technical expertise alone is not enough. What often distinguishes strong candidates is the ability to tell a clear story about the data or model and to communicate insights effectively to different audiences. In today’s workplace, being able to translate technical analysis into practical understanding is a major advantage.
The panelists were optimistic about AI and its impact on their work. They described AI as a tool that increases productivity and helps them take on problems outside their immediate technical expertise. By combining strong problem framing with AI-assisted tools, professionals can develop solutions more quickly and more creatively.
When discussing what sets job candidates apart, the panelists pointed to several qualities: a sophisticated understanding of technical tools, grit in tackling challenging problems, friendliness, and humility. Together, these traits help candidates stand out in a competitive and fast-changing field.
Panelists
- Christopher J. Daigle, Associate Vice President (AVP) of AI & Automation Engineering at Arch Capital, MSQE 2018
- Sean Ippolito, Senior Data Scientist for Identity & Fraud Services, Equifax
- Neal Coleman, PhD, Data Scientist and Director of Emerging Sciences, The Hartford
- Moderator: Oskar Harmon, Associate Professor of Economics
If you missed this panel, there will be more opportunities in the future. We look forward to hosting additional panels that connect students with professionals working at the forefront of AI and quantitative economics.




Along with collaborators at Syracuse University, Johns Hopkins University, UC Merced, and Georgetown University,
The presentation examined the integration of Tableau-based data visualization into a required undergraduate economics writing course. Using pre- and post-course survey data, the study finds improvements in student course satisfaction and writing confidence after students learned to produce their own data visualizations. The results highlight the potential for combining data literacy and writing instruction to enhance student engagement and communication skills in economics coursework.
Neither final exams nor frigid temperatures stopped faculty and PhD students from running the