Thomas Howley is an experienced finance professional with a strong background in data modeling, analytics, and forecast development. Currently serving as the Strategic Finance Data Modeling Manager at Affirm, Thomas has designed and implemented Python-based financial forecasting and automated ETLs utilizing SQL and Python. Prior to Affirm, Thomas was a Quantitative Analytics Specialist at Wells Fargo, focusing on statistical forecasts for credit risk modeling using Python and big data technologies like PySpark and Hadoop. Thomas also served as a Risk Analyst at U.S. Bank, where Python was used for data stratification and automation. Thomas began the career at U.S. Bank as a Graduate Intern, applying database query design to foreign exchange transactions and creating a Python application for data analysis. Education includes a Master's degree in Quantitative and Computational Finance from Georgia Tech Scheller College of Business, a Bachelor of Science in Mathematics and Computer Science from Stockton University, and a Bachelor's degree in Economics from Rutgers University.
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