Lead Quantitative Modeler - Prepayment Models

Fannie Mae • Washington, DC

8d • $141,000 - $184,000

About The Position

As a valued colleague on the team, the Lead Quantitative Modeler acts as a team lead conducting theoretical and empirical research with public and proprietary data across mortgage finance. The role applies expertise in economics, statistics, time-series modeling, and advanced machine learning to develop predictive models, improve risk-management strategies, and generate actionable insights. The role also coaches and mentors team members.

Research areas may include mortgage products and securities, borrower behavior, investment and hedging strategies, residential property valuation, macroeconomic models such as housing prices and interest rates, financial valuation of assets and derivatives, economic capital, and stress testing. The position supports retained portfolio whole-loan behavioral and cash-flow models, especially for non-performing and re-performing loans, as well as mortgage-backed securities prepayment models. It uses model outputs to analyze cash flows, valuation, and risk measures, and collaborates with business stakeholders and technical teams to develop, validate, implement, and document models in accordance with regulatory requirements and internal policies.

Requirements

• At least 4 years of experience developing and implementing agency MBS prepayment, transition/termination, survival or time-to-event, multinomial/logistic, or other credit-risk and behavioral models.
• Strong understanding of statistical modeling, model calibration, backtesting, benchmarking, sensitivity analysis, scenario analysis, and stress testing.
• Strong written and verbal communication skills, including explaining technical concepts to quantitative and nontechnical audiences.
• Advanced programming skills, particularly in Python, and ability to develop scalable analytical solutions.
• Curiosity and adaptability in learning and responsibly applying new technologies, including artificial intelligence.
• Bachelor's degree or equivalent in Economics, Statistics, Computer Science, or a related quantitative field; the education section lists a bachelor's-level degree as required.

Nice To Haves

• Advanced degree preferred.
• Strong understanding of mortgage borrower behavior and credit performance, including delinquency progression, cure/re-default, modification/forbearance, prepayment, liquidation, recovery timing, and loss severity.
• Strong understanding of fixed-income valuation and mortgage cash-flow modeling, including discounted cash flow, interest-rate sensitivity, duration, convexity, and related risk analytics.
• Experience with Python libraries and frameworks such as TensorFlow, PyTorch, and scikit-learn.
• Experience building user interfaces for analytics tools in an AWS environment.
• Strong knowledge of AI/ML and experience applying AI/ML models to mortgage and loan modeling.
• Experience with AI workflows for quantitative modeling and/or software engineering.
• Proven ability to collaborate with Capital Markets, model users, risk, technology, and governance teams; manage multiple projects and deliver high-quality work under tight deadlines.

Responsibilities

• Lead teams in delivering practical quantitative solutions supporting business strategies and initiatives, and conduct or assess ad hoc quantitative analyses, modeling, and programming.
• Coach and mentor team members in data mining and statistical techniques, helping develop analytic insights, hypotheses, and recommendations; identify opportunities to improve business performance through quantitative methods.
• Lead modeling projects in line with company policies and industry modeling practices.
• Contribute to model validation and testing strategies; assess model methodologies, outputs, processes, and risks; interpret results in business context and monitor model performance.
• Communicate technical subject matter clearly to department leadership and teams.
• Analyze economic indicators, market trends, borrower behavior, and macroeconomic factors to inform modeling assumptions, parameter estimates, cash-flow forecasts, and scenarios.
• Support development and implementation of retained portfolio whole-loan behavioral and cash-flow models, with emphasis on non-performing and re-performing loans.
• Build and evaluate model-ready loan-level datasets; perform variable selection, calibration, backtesting, benchmarking, sensitivity testing, and model performance analysis.
• Translate behavioral model outputs into cash flows and assess valuation and risk measures, including duration, key-rate duration, and convexity; reconcile and benchmark results across models and implementations.
• Support development and implementation of MBS prepayment models.
• Use AI/ML-enabled tools and advanced analytical techniques where appropriate to accelerate model research, coding, testing, documentation, and implementation while maintaining controls and model governance.
• Collaborate with Capital Markets stakeholders, data scientists, economists, risk managers, and other cross-functional partners to gather requirements, define scope, and drive model development.
• Develop and maintain documentation, code repositories, and model validation reports in compliance with regulatory requirements and internal policies.
• Stay current with trends and best practices in quantitative finance, econometrics, statistics, and machine learning, applying them to improve modeling capabilities.

Benefits

• Broad range of health, life, voluntary lifestyle, and other benefits and perks supporting physical, mental, emotional, and financial well-being.
• Eligible to participate in a Fannie Mae incentive program, subject to its terms.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior