William Crimmins
About William Crimmins
William Crimmins is a Senior Business Analyst in the Climate Impact Division at Fannie Mae, with a background in applied economics and extensive experience in research and data analysis.
Title and Current Role at Fannie Mae
William Crimmins holds the position of Senior Business Analyst in the Climate Impact Division at Fannie Mae. He is currently based in the Washington D.C. Metro Area. In this role, he engages with projects that focus on the intersection of business analysis and climate impact, leveraging his expertise in data modeling and quantitative analysis.
Past Experience at Hanover Research
Between 2016 and 2018, William Crimmins worked at Hanover Research as a Research Associate specializing in Higher Education. During his two-year tenure in Arlington, Virginia, he conducted in-depth research and provided actionable insights to educational institutions, enhancing their strategic decision-making processes.
Education and Degrees
William Crimmins has a robust academic background. He earned a Master of Science (MS) in Applied Economics from Johns Hopkins University Advanced Academic Programs, studying from 2020 to 2022. Prior to that, he obtained a Bachelor's degree in Econometrics and Quantitative Economics from the University of Colorado Boulder, studying from 2012 to 2015. Additionally, he studied Economics at George Mason University for one year from 2011 to 2012. His foundational education was completed at Lakewood High School.
Technical Proficiency and Cloud Transition
William Crimmins has demonstrated significant technical proficiency, particularly in developing modeling applications using R and Python. This includes creating GUIs, Shiny Dashboards, and custom-built packages. He played a pivotal role in transitioning applications to AWS Cloud Services, serving as the lead AWS Certified Developer, showcasing his capability in modern cloud-based solutions.
Leadership and Training
At Fannie Mae, William Crimmins provided extensive training and support for over 200 downstream internal clients. He also led a team in a distressed asset valuation hackathon, where they distinguished themselves by finishing in the top 10 and notably improving production prediction error by 30%.