Lead Quantitative Modeler - Prepayment Models

The Fannie Mae; Washington (District of Columbia); Presencial; USD 141.000 - 184.000; Jornada completa

Descripción de la vacante

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

Formación

• 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.

Responsabilidades

• 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.

Conocimientos

Agency MBS modeling

Statistical modeling

Python programming

Communication skills

AI adoption

Educación

Bachelor's degree in economics/statistics/computer science

Advanced degree preferred

Herramientas

Python

TensorFlow

PyTorch

scikit-learn

Descripción del empleo

Playing an essential role in the U.S. economy, Fannie Mae is foundational to housing finance. Here, your expertise can help fuel purpose-driven innovation that expands access to homeownership and affordable rental housing across the country. Join Fannie Mae to grow your career and help people find a place to call home.

Job Description

As a valued colleague on our team, you will act as team lead while conducting theoretical and empirical research with public and proprietary data in all areas of the mortgage finance business. This may include mortgage products and securities, borrower behavior, investment and hedging strategies, residential property valuation, macroeconomic models, including housing prices and interest rate, financial valuation of finance assets and derivatives, economic capital, and stress testing. Additionally, you will coach and mentor team members. You will be responsible for leveraging expertise in economics, statistics (with a focus on time-series modeling), and advanced machine learning to develop predictive models, optimize risk management strategies, and drive actionable insights. You will also act as team lead while conducting theoretical and empirical research with public and proprietary data in all areas of the mortgage finance business. This may include mortgage products and securities, borrower behavior, investment and hedging strategies, residential property valuation, macroeconomic models, including housing prices and interest rate, financial valuation of finance assets and derivatives, economic capital, and stress testing.

The Impact You Will Make

Responsibilities

• Lead teams in providing innovative, thorough, and practical solutions that support business strategies and initiatives and in conducting or assessing ad hoc quantitative analyses, modeling, or programming using Python, SQL, R, or SAS.
• Coach and mentor team members in utilizing data mining and/or statistical techniques to develop analytic insights, sound hypotheses, and informed recommendations. Identify opportunities to apply quantitative methods to improve business performance.
• Apply advanced skill, knowledge, and/or experience while leading teams to complete modeling projects aligned with established company policies and industry-wide modeling practices.
• Contribute to developing validation or testing strategies and assessing the quality and risk of model methodologies, outputs, and processes and applying understanding of relevant business context to interpret model results, monitor performance, and assess risks.
• Communicate technical subject matter clearly and concisely to department leadership and teams.
• Conduct in-depth analysis of economic indicators, market trends, borrower behavior, and macroeconomic factors to inform modeling assumptions, parameter estimates, cash-flow forecasts, and scenario analysis.
• Support the development and implementation of retained portfolio whole-loan behavioral and cash-flow models, with emphasis on non-performing (NPL) and re-performing (RPL) loans.
• Build and evaluate model-ready loan-level datasets and perform variable selection, calibration, in-sample/out-of-sample backtesting, benchmarking, sensitivity testing, and model performance analysis.
• Translate behavioral model outputs into cash flows and assess impacts on valuation and risk measures such as duration, key-rate duration, and convexity; reconcile and benchmark results across models and implementations.
• Support the development and implementation of MBS prepayment models.
• Apply AI/ML-enabled tools and advanced analytical techniques, where appropriate, to accelerate model research, coding, testing, documentation, and implementation while maintaining appropriate controls and model governance.
• Collaborate closely with cross-functional teams, including business stakeholders in Capital Markets, data scientists, economists, and risk managers to gather requirements, define project scope, and drive model development efforts.
• Develop and maintain documentation, code repositories, and model validation reports in compliance with regulatory requirements and internal policies.
• Stay current with emerging trends, methodologies, and best practices in quantitative finance, econometrics, statistics, and machine learning, and apply them to enhance modeling capabilities and stay ahead of the curve.

As a valued colleague on our team, you will act as team lead while conducting theoretical and empirical research with public and proprietary data in all areas of the mortgage finance business. This may include mortgage products and securities, borrower behavior, investment and hedging strategies, residential property valuation, macroeconomic models, including housing prices and interest rate, financial valuation of finance assets and derivatives, economic capital, and stress testing.

Minimum Required Experiences

The Experience You Bring To The Table

• 4 years of proven experience in 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 the ability to explain technical concepts to both quantitative and nontechnical audiences.
• Advanced programming skills, particularly in Python, with the ability to develop scalable analytical solutions.
• Shows curiosity and adaptability in learning and responsibly applying new technologies, including artificial intelligence, to reimagine how we work.
• Shows curiosity and adaptability in learning and responsibly applying new technologies, including artificial intelligence, to reimagine how we work.

Desired Experiences

• Bachelor degree or equivalent in Economics, Statistics, Computer Science, or a related quantitative field. 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.
• Strong programming skills in Python, experience with relevant libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Experience in building UI for analytics tools in AWS environment a strong plus.
• Strong knowledge in AI/ML and experienced with AI/ML models for mortgage and loan modeling.
• Experienced 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 results under tight deadlines.

Target Pay Range

$141,000.00 – 184,000.00 a year

Internal Job Title

Enterprise Modeling and Analytics - Quantitative Modeling - Lead Associate

Qualifications

Credit Risk Modeling, Data Analytics, Machine Learning (ML), Mortgage Analytics, Prepayment, Python (Programming Language)

Education

Bachelor's Level Degree (Required)

The future is what you make it to be. Discover compelling opportunities at Fanniemae.com/careers.

For most roles, employees are expected to work onsite on a regular basis at their designated office location. In-office work cadence is determined by your manager. Proximity within a reasonable commute to your designated office location is preferred unless the job is noted as open to remote.

Fannie Mae is an equal opportunity employer and considers qualified applicants for employment without regard to race, color, religion, sex, national origin, disability, age, sexual orientation, gender identity/gender expression, marital or parental status, or any other protected factor. Fannie Mae is committed to providing reasonable accommodations to qualified individuals with disabilities who are employees or applicants for employment, unless to do so would cause undue hardship to the company. If you need assistance using our online system and/or you need a reasonable accommodation related to the hiring/application process, please complete this form.

The hiring range for this role is set forth below. Final salaries will generally vary within that range based on factors that include but are not limited to, skill set, depth of experience, certifications, and other relevant qualifications. This position is eligible to participate in a Fannie Mae incentive program (subject to the terms of the program). As part of our comprehensive benefits package, Fannie Mae offers a broad range of Health, Life, Voluntary Lifestyle, and other benefits and perks that enhance an employee's physical, mental, emotional, and financial well-being. See more here.

Requisition Compensation

141000 to 184000