Risk Management Graduate Intern Quantitative Summer

At Freddie Mac, our mission of Making Home Possible is what motivates us, and it's at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose.

We are accepting applications for this position until 10/16/2026 Position Overview: At Freddie Mac, you will have meaningful work to help build a better housing finance system and support home ownership and rental housing opportunities across the nation. Our internship and graduate programs provide opportunities to tackle complex challenges, contribute to strategic initiatives, and build valuable relationships with industry professionals. As a Quantitative Risk Management Intern within Enterprise Risk Management (ERM), you will apply advanced analytical, technical, and quantitative skills to support risk management activities at one of the nation's largest financial institutions.

You will gain hands-on experience working on real-world projects, collaborating across teams, and leveraging emerging technologies - including artificial intelligence and automation - to enhance risk management practices and business outcomes. Our Impact: Enterprise Risk Management (ERM) helps build and maintain a strong, effective, and efficient risk management framework across Freddie Mac. We provide independent oversight and assessment of financial and non-financial risks while promoting a culture of accountability, innovation, and sound risk management.

Our quantitative teams leverage advanced analytics, data science, modeling, automation, and emerging technologies to support enterprise-wide decision-making and risk oversight. As AI and automation continue to transform the financial services industry, our teams play a critical role in helping Freddie Mac navigate evolving risks while identifying opportunities for efficiency and Your Impact: Project Support As an intern, you will support projects that contribute to Enterprise Risk priorities, which may include: Execute quantitative and analytical projects while ensuring timely delivery, adherence to objectives, and effective management of project scope. Develop, evaluate, and utilize quantitative models and analytical tools to support assessment of market, credit, operational, and emerging risks.

Collaborate with risk, business, and technology teams to solve complex problems and drive data-driven decision-making. Support model development, validation, monitoring, and evaluation activities across various risk disciplines. Apply programming, data analysis, and automation techniques to improve efficiency and enhance quantitative processes.

Analyze large and complex datasets to identify trends, assess risk exposure, and support strategic initiatives. Partner with stakeholders across the organization and serve as a point of contact for project-related activities and information gathering. Contribute to initiatives involving AI, automation, cloud technologies, and advanced analytics.

Support process improvement efforts, documentation, reporting, and governance activities. Professional Development Participation in the program will support your continued growth through targeted training, mentorship, and exposure to senior leadership. You will: Gain exposure to Freddie Mac's standards, processes, risk frameworks, and governance structures.

Strengthen your quantitative, analytical, technical, and leadership capabilities. Build relationships across ERM and the broader Freddie Mac organization Learn how quantitative risk management supports enterprise decision-making and business strategy. Develop a deeper understanding of AI applications, automation, and risk analytics within the financial services industry.

Qualifications: Enrolled in a full-time graduate degree program in Data Analytics, Computer Science, Applied Mathematics, Statistics, Financial Engineering, Econometrics, Quantitative Finance, Artificial Intelligence, Machine Learning, Economics, or a related quantitative field. One to three years of professional work experience. Expected graduation date of December 2027 or May 2028.

Preferred Skills Strong programming experience in Python, Java, C++, SQL, or similar languages.

Experience working with large datasets and performing complex quantitative analysis. Familiarity with cloud computing platforms and modern data technologies. Knowledge of AI, machine learning, automation, data validation, or advanced analytics techniques Experience…