Risk Management Graduate Intern – Quantitative Summer 2027

Freddie Mac•McLean, VA

11d•Onsite

About The Position

At Freddie Mac, you will have meaningful work to help build a better housing finance system and support homeownership 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.

Requirements

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.

Nice To Haves

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 with financial modeling, risk modeling, econometrics, statistics, or related quantitative disciplines.
Proficiency with Microsoft Office applications, including Excel and PowerPoint.
Experience with Tableau, MicroStrategy, Power BI, or other data visualization tools is a plus.
Exposure to banking, financial services, risk management, or consulting environments is beneficial.

Responsibilities

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.