Job Description
With Fannie Mae’s 10-week (June 2025 - August 2025) paid internship program you will be empowered to drive change, lead with creativity, own your career, and make a difference. As a path to our full-time opportunities, you will be a true contributor on a team that fits your skills and interest in a dynamic environment alongside our employees.
THE IMPACT YOU WILL MAKE
As an intern on our Analytics team, you will develop and apply analytical skills by researching open-ended questions, leveraging our data to produce insights, and providing consultative services to extend Fannie Mae’s dynamic credit risk management capabilities.
You will participate in a one-week seminar style training of both business information and technical skills. The business courses provide exposure to key business areas at the company and the role of analytics in supporting them. The technical courses include SQL, Python, and R, as well as an introduction to working with technology and data platforms, including Redshift, Domino Data Lab, and Git/Bitbucket.
Examples of intern tasks and projects include:
- Developing a metric to aid in our mission to facilitate equitable and sustainable access to homeownership
- Researching production model improvements through back-testing, text analysis, and data mining
- Investigating techniques to identify anomalous data across metrics and within varying loan populations
- Collaborate with fellow Analytics Interns on Data Science hackathons in areas including Logistic Regression Modeling and GenAI.
Qualifications
THE EXPERIENCE YOU BRING TO THE TEAM
Minimum Qualifications
- Be authorized to work in the U.S. without sponsorship
- Academic achievement (preferred GPA of 3.2 or above)
Preferred Qualifications
- Rising senior enrolled in a bachelor’s degree program (2026 graduation date)
- Mathematics, Statistics, Computer Science, Systems Engineering, Economics with a quantitative focus, and Data Science majors are preferred
- Open and honest communicator with demonstrated leadership capabilities
- Quantitatively-minded with an aptitude for analytical story-telling
- Fluent with technology applications and excited to learn new technologies
- Demonstrated problem-solving with a solutions-oriented approach
- A self-starter who’s comfortable asking questions and persevering through unforeseen challenges