Andrew Kerzak is a Ticketing, Inventory, Pricing and Data Analyst at Churchill Downs Racetrack in Louisville, Kentucky. He was a 2023 Master of Quantitative Economics (MQE) graduate. During his time in the MQE program, he completed a data analytics capstone project with Sheetz, where he created models to forecast sales for their Made-to-Order Products for each store across the Sheetz Pittsburgh footprint. Prior to coming to the University of Pittsburgh, Andrew completed his Bachelor’s degree in economics from West Virginia University. As an undergraduate, Andrew completed a data analytics undergraduate capstone project with the West Virginia Economics Department and had an internship with the Philly Pretzel Factory. In his undergraduate capstone, he modeled team wins to gauge competitiveness across Major League Baseball using historical data. In his internship he interpreted business revenue data and used that information to facilitated revenue growth to keep the business open during the Covid-19 pandemic. Read more about Andrew and his time in the MQE program:
How has the MQE program provided you with the skills needed to succeed in your current position as a Ticketing, Inventory, Pricing and Data Analyst at Churchill Downs Racetrack?
The MQE program provided me with the needed skills to succeed with the Churchill Downs Racetrack through a project-based learning system. Throughout my year in the program, I completed numerous projects analyzing a diverse array of problems. From predicting the winner of the Super Bowl to analyzing the impacts of tax rates in Wilkinsburg, PA. Looking at different problems like these allowed me to use my tools in new ways that helped me to master the skills needed to succeed after graduation. Now that I am presented with new questions from different sources in my real-world job it is nice to have the experiences of the MQE program to efficiently find solutions.
What did you love learning about the most during your time in the MQE program?
I loved learning about machine learning models and how to effectively visualize data during my time in the MQE program. By far my favorite class during my year in the MQE program was Big Data and Forecasting in Economics. This class spent the 8-week course surveying numerous machine learning models and implementing them while learning a new programming language, Python. Gaining experience with machine learning models has changed the way I approach problem-solving and has become one of my favorite tools. In terms of data visualization, the MQE program provided many opportunities to create visualizations like bar charts/scatter plots, and present to diverse audiences from your cohort and professor to your capstone project liaisons. I enjoyed that the program had us creating visualizations from the first days of basecamp to the final days of the capstone project.
How did you implement skills from the MQE program into your capstone project with Sheetz?
We implemented our MQE program skills of data visualization, modeling/forecasting, and presentation skills in our Sheetz capstone project. For the majority of the project, my capstone group explored the dataset using our data visualization skills to gain as much insight as possible prior to writing models. After spending many weeks implementing our visualization skills we used our experiences modeling and forecasting from previous classes combined with our knowledge of the data set gained from the exploration stage to write an accurate forecast for MTO Sales. After completing the analysis, we finished the project using our polished presentation skills to present the results to the data analytics team at Sheetz.
How did the MQE program help prepare you for real-world job/career experience?
The MQE program helped me prepare for my real-world job through growing and testing my technical skills, pushing me to stand up and present as much as possible, and helping me build many lasting relationships in the Pittsburgh area and analytical community. The MQE program was the perfect place to not only test my previous coding/technical skills but also to explore new skills such as Python, Jupyter Notebooks, and SQL. Mastering these different software systems has allowed me to maximize my analytical capabilities using a diverse technical skillset. Next, the program’s emphasis on communication was a key driver in my decision to attend the University of Pittsburgh and has been vital in my success post-graduation. Six weeks into my full-time position I was standing up in front of the executive team to present my analytical results, which would have daunted me prior to Pitt. Attending communications class and presenting every week not only reduced my presentation fears but help me build confidence. Finally, the MQE program was great for building lasting relationships not only within the cohort but also with members of the Advisory Board, the Pittsburgh community, and the faculty.