Senior Quantitative Modeling Lead – Mortgage Analytics

The Fannie Mae; Washington (District of Columbia); Sur place; USD 141 000 - 184 000; Plein temps

Résumé du poste

Fannie Mae in Washington, DC seeks a leader for Enterprise Modeling and Analytics to guide quantitative research and model development across mortgage finance. You will supervise teams applying time-series econometrics and machine learning to mortgage products, borrower behavior, and risk management, while mentoring staff and ensuring governance.

The role emphasizes cross-functional collaboration with Capital Markets, economists, data scientists, and risk managers to deliver robust model

Qualifications

• 4 years of proven experience in developing and implementing agency MBS prepayment and related models.
• Strong understanding of statistical modeling, calibration, backtesting, benchmarking, and stress testing.
• Advanced programming skills, particularly in Python, with scalable analytics.
• Ability to explain complex concepts to technical and nontechnical audiences.
• Willingness to learn and responsibly apply AI technologies in modeling.

Responsabilités

• Lead teams in innovative quantitative analyses, modeling, or programming using Python, SQL, R, or SAS.
• Coach and mentor team members to develop analytic insights and recommendations.
• Develop validation strategies and assess model risk and performance.
• Translate model outputs into actionable insights for valuation and risk metrics.
• Collaborate with Capital Markets, data scientists, economists, and risk managers to drive model development.

Connaissances

Agency MBS modeling

Statistical modeling

Python programming

Communication skills

AI adoption

Formation

Bachelor's degree in economics/statistics/computer science

Advanced degree preferred

Outils

Python

TensorFlow

PyTorch

scikit-learn

Description du poste

Fannie Mae in Washington, DC seeks a leader for Enterprise Modeling and Analytics to guide quantitative research and model development across mortgage finance. You will supervise teams applying time-series econometrics and machine learning to mortgage products, borrower behavior, and risk management, while mentoring staff and ensuring governance.

The role emphasizes cross-functional collaboration with Capital Markets, economists, data scientists, and risk managers to deliver robust model