Kelley Carstons
About Kelley Carstons
Kelley Carstons is a Senior Data Science Associate at Fannie Mae with a background in Economics and History from the University of Virginia.
Current Title: Senior Data Science Associate
Kelley Carstons currently holds the position of Senior Data Science Associate at Fannie Mae. In this role, she leverages her expertise in data analysis to contribute to the company's data-driven decision-making processes. With a background in economics and history, Kelley brings a unique perspective to her data science work, which enhances her ability to interpret complex data sets and generate actionable insights.
Career Progression at Fannie Mae
Kelley Carstons has built a comprehensive career at Fannie Mae, progressing through various roles since 2018. She started as a Financial Engineer and then transitioned to a Credit Risk Associate in the Washington D.C. Metro Area. Following this, she served as an Analytics and Modeling Associate and then as a Data Science Associate from 2021 to 2023. Her diverse roles have provided her with a well-rounded understanding of credit risk, analytics, and financial engineering, which she now applies in her current senior role.
Educational Background in Economics and History
Kelley Carstons studied Economics and History at the University of Virginia, where she earned her Bachelor of Arts (B.A.) from 2015 to 2019. She also attended a short study program at the University of Amsterdam in 2017. Her academic background in both fields provides her with a strong foundation for her data science activities, enabling her to approach problems from multifaceted perspectives.
Experience in Credit Risk and Analytics
Throughout her tenure at Fannie Mae, Kelley has amassed substantial experience in credit risk and analytics. She worked as a Credit Risk Associate from 2019 to 2020 before transitioning into roles that focused more on analytics and data modeling. Her responsibilities included assessing credit risk and developing predictive models to improve the company's financial decisions. This robust experience has been critical to her development as a Senior Data Science Associate.