Risk Management Graduate Intern – Quantitative Summer 2027

Freddie Mac is a financial institution focused on supporting the housing finance system, homeownership, and rental housing opportunities. The Quantitative Risk Management Graduate Intern will support Enterprise Risk Management projects by developing and evaluating quantitative models, analyzing complex datasets, collaborating across teams, and applying AI, automation, and advanced analytics to risk management. The role also provides training, mentorship, and exposure to risk frameworks and governance.

What you'll do:

• 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
• 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

What they're looking for:

• 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
• Strong critical-thinking and analytical problem-solving abilities
• Curiosity and willingness to ask thoughtful questions to deepen business understanding
• Excellent written, verbal, and interpersonal communication skills
• Ability to collaborate effectively across teams and build strong professional relationships
• Execution focus, personal accountability, and strong organizational skills
• Ability to manage multiple priorities, deliver results, and maintain project focus under changing conditions
• Adaptability and comfort working through ambiguity while developing innovative solutions
• Interest in leveraging AI and automation to improve efficiency and business outcomes while understanding the limitations of emerging technologies
• A proactive mindset and passion for continuous learning and improvement

Benefits:

• Targeted training
• Mentorship
• Exposure to senior leadership