Rory Quinlan was a 2025 Master of Quantitative Economics (MQE) graduate from the University of Pittsburgh and earned a Bachelor of Science in Economics and Statistics in 2024, also from Pitt. While at Pitt, she was a Financial Educator and a Data Analytics Team Lead as well as a Research Assistant and Teaching Assistant. Her MQE capstone where she served as a Data Consultant with Blue Street Data, where they analyzed thousands of U.S. public sector job postings scraped from the USAJOBS public API to identify roles that are likely engaged in purchasing or using third party data. Rory currently works at the Federal Reserve Bank of Cleveland as a Research Analyst. Her primary research interests are econometrics, forecasting, and computational methods. Read more about Rory below:
How did you decide on the University of Pittsburgh and your majors in Economics and Statistics? Did you have any favorite classes in Economics?
I chose the Economics-Statistics dual major because of the combination of practical application and theoretical depth. The economics curriculum taught me to think critically and approach real-world problems with rough frameworks, while the statistics curriculum provided the theoretical foundation for the modeling techniques I use. Few university programs today offer this combination of skills. The Economics-Statistics major gave me the perspective and quantitative theory I use to address my research challenges.
My favorite economics class I took at the university was Game Theory. It was my first exposure to integrating more advanced math concepts within the econ domain. This class was a big turning point for me, as I realized I was interested in the statistical methods underlying the economic concepts we studied, which led me toward my current research interest in econometrics.
What made you decide that the MQE program was right for you?
I found that each class I took left me with new questions. By my senior year of undergrad, I knew there was still too much left to learn to end my education there, so I decided to continue it with the MQE.
What did you love learning about the most during your time in the MQE program?
I enjoyed learning about machine learning applications in economics. There is an entire frontier of research on how, where, and when to apply these models to answer economic questions.
How did the MQE program help prepare you for real-world job/career experience?
For my capstone project, I was paired with a Pittsburgh tech start-up, Blue Street Data, and was given a broad question: “How can we describe the data buyer market?” With that, I was given free rein to develop a framework to identify demand and quantify leads. In my career, I develop research questions and design methodologies to answer them as thoroughly and rigorously as possible. My capstone project was an excellent experience conducting this process as part of a professional team.