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Quantitative Engineering Opportunities at Fannie Mae (Associate to Management Levels) – (Flexible Hybrid)

Company Description

At Fannie Mae, futures are made. The inspiring work we do helps make a home a possibility for millions of homeowners and renters. Every day offers compelling opportunities to impact the future of the housing industry while being part of an inclusive team thriving in an energizing, flexible environment. Here, you will grow your career and help create access to fair, affordable housing finance.

Job Description

Job Type: Quantitative Engineer (Associate to Management Levels)

Are you passionate about quantitative engineering, mortgage finance, business and risk analytics? Fannie Mae is expanding its talent pool for multiple Quantitative Engineering roles to work on the model application development in following areas:

• Single-Family and Multi-Family Mortgages Loan and Pool Performance Modeling

• Borrower Behavioral and Loss Severity Mitigation Modeling
• Market, Liquidity, Term Structure Interest Rate and Mortgage Rate Modeling

• Interest Rate Derivative Pricing

• Macroeconomic and Time Series Modeling

• Regional and National Home Price Forecasting

• Capital Markets & Structured Finance

• Back-end Credit Enhancement

• Enterprise Risk Management

• Stress Testing (Management Stress Test and Dodd Frank Stress Test)
• Financial Reporting (Fair Value, CECL Allowance, Revenue, Capital)

• Model Performance Monitoring and Remediation

• Model data and analytics visualization for decision making


Who We’re Looking For:

Fannie Mae is seeking talented quantitative professionals at various levels, from associate quantitative engineers to managers, to help drive data-driven and model-guided decision-making at Fannie Mae. If you are an experienced software developer and tester (preferably of modeling applications), quantitative engineer, financial and mortgage risk analyst, or data scientist, we encourage you to apply.

Key Responsibilities:

Depending on the specific team and role, responsibilities may include:

  • Analyze business requirements, design solution, develop and test model application, release to production and provide operation and customer support.
  • Implement and refine quantitative models to forecast macro-economic environment and mortgage loan performance, assess company financials and capital requirement, and manage enterprise risks including interest rate risk, prepayment risk, credit risk, market risk, model risk, operation risk.
  • Apply sophisticated statistical and machine learning techniques to improve model coverage and performance.
  • Design and conduct model user vetting including scenario analysis, sensitivity analysis, stress testing, attribution analysis, back testing, etc.
  • Design and perform software development testing including unit-test, regression test, reconciliation, system integration test, shakeout, user acceptance test, etc.
  • Collaborate with cross-functional teams from various business users, product and project managers, model owners and developers, model validators, internal audit, and external consultants.
  • Ensure compliance of FHFA directives, Basel, Industry and Fannie Mae’s model risk policy and management standards.
  • Ensure compliance of System Development Life Cycle (SDLC) standards and enterprise data policy and governance.
  • Present findings and recommendations to 2nd-/3rd-Lines of Defense, senior leadership and regulators.
  • Monitor and adapt to technology advancement and industry best practices in model and software development.
  • (Management Level) Manage a team of quantitative engineers and oversee the E2E Model and Software Management Life Cycle to deliver production-quality software to meet business needs.

 

Qualifications

Qualifications:

  • Education: Bachelor (must-have), Master (preferred), or Ph.D. (a plus). in Computer Science, Software Engineering, Data Science, Information Technology, Quantitative Finance, Statistics, Mathematics, or related fields.
  • Technical Skills: Proficiency in a popular programming languageincluding Python, Java, R, R-Shiny, SQL, C++, Linux Shell Scripts. Software developer in Linux and Windows environments on AWS platform. EEngineering, econometrics, statistical and analytical skills. Largescale model application development.Big data analysis. .
  • Soft Skills: Strong problem-solving attitude and result driven. Self-driven learner and independent thinker. Team player and leader with compassion. Proactive and efficient communication verbally and in writing with various stakeholders including business and technology partners, reviewers, peers and senior management.
  • Mortgage Finance Knowledge: Experience or knowledge in single-family or multifamily mortgage models, MBS, macro-economic and financial modeling, credit default risk, or capital markets risk.
  • Experience Level: Open to early-career (2yr+), mid-career (4yr+), and managerial candidates with relevant experience in quantitative and software engineering, modeling and analytics development and management.

Why Join Fannie Mae’s Talent Pool?

By joining this talent pool, you will:

  • Be considered for multiple quantitative engineering roles across different Engineering teams at Fannie Mae.
  • Work on high-impact projects shaping the U.S. housing finance system.
  • Gain exposure to cutting-edge technologies and practices in quantitative finance, modeling and engineering.
  • Enjoy career growth, mentorship, and leadership development opportunities.

Apply now to be considered for upcoming Quantitative Engineering roles at Fannie Mae!

**Please note that this invitation is NOT an active opening/positing. Applying constitutes an expression of interest in future similar active openings at Fannie Mae. A recruiter will review your qualifications and, if an active opening becomes available in the future that meets your skill set, you may be contacted. **

Additional Information

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

Fannie Mae is an Equal Opportunity Employer, which means we are committed to fostering a diverse and inclusive workplace. All qualified applicants will receive consideration for employment without regard to race, religion, national origin, gender, gender identity, sexual orientation, personal appearance, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation in the application process, email us at [email protected].
 

The hiring range for this role is set forth on each of our job postings located on Fannie Mae's Career Site. 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.

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What You Should Know About Quantitative Engineering Opportunities at Fannie Mae (Associate to Management Levels) – (Flexible Hybrid), Fannie Mae

Join Fannie Mae as a Quantitative Engineer, where our mission is to make homeownership possible for millions. Based in Washington, DC, this role encompasses various levels, from associates to management, offering a flexible hybrid work environment. If you're passionate about quantitative engineering, mortgage finance, and leveraging data for risk analytics, we want you! In this position, you’ll have the opportunity to contribute to key projects like modeling mortgage performance, conducting stress testing, and enhancing risk management strategies. You'll work with cross-functional teams, analyze business requirements, and refine quantitative models to forecast financial trends and manage enterprise risks. Whether you're an experienced software developer, a risk analyst, or a data scientist, we encourage you to share your expertise and ideas. At Fannie Mae, you’ll not only help shape the housing finance landscape but also grow your career in an engaging, supportive environment. If you’re ready to make an impact, we invite you to apply and become part of a team that values collaboration, innovation, and community. Fannie Mae is committed to fostering a diverse and inclusive workplace where you can thrive. Let's shape the future of housing finance together!

Frequently Asked Questions (FAQs) for Quantitative Engineering Opportunities at Fannie Mae (Associate to Management Levels) – (Flexible Hybrid) Role at Fannie Mae
What are the main responsibilities of a Quantitative Engineer at Fannie Mae?

As a Quantitative Engineer at Fannie Mae, your duties will include analyzing business requirements, developing and testing model applications, and supporting operational needs. You will be involved in model creation for mortgage loan performance forecasting, risk management, and conducting scenario analyses. Additionally, you will collaborate with various teams, ensuring compliance with regulatory standards and leveraging advanced statistical techniques to enhance model performance.

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What qualifications are required for Quantitative Engineering roles at Fannie Mae?

Fannie Mae seeks candidates with a Bachelor’s degree in Computer Science, Statistics, Mathematics, or related fields. Preferred candidates may possess a Master's degree or a Ph.D. Proficiency in programming languages like Python, R, and SQL, as well as experience in statistical and analytical methodologies, is essential. Relevant experience in mortgage finance and risk analytics will also enhance your application.

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What types of projects will I work on as a Quantitative Engineer at Fannie Mae?

In the Quantitative Engineer role at Fannie Mae, you will engage in impactful projects such as developing models for forecasting housing market trends, mortgage performance, and capital risk management. You will also be responsible for stress testing and ensuring compliance with financial regulations while applying state-of-the-art techniques in quantitative finance.

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How does Fannie Mae support professional growth for Quantitative Engineers?

Fannie Mae is dedicated to the professional development of Quantitative Engineers. You will have access to mentorship programs, leadership opportunities, and training on emerging technologies and quantitative practices. The inclusive environment fosters collaboration and supports career advancement across various engineering teams.

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What is the work environment like for Quantitative Engineers at Fannie Mae?

At Fannie Mae, the work environment for Quantitative Engineers is dynamic and collaborative. You’ll enjoy a flexible hybrid setting that promotes a strong work-life balance. The culture emphasizes innovation, teamwork, and the shared mission of making housing finance more accessible and equitable.

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Common Interview Questions for Quantitative Engineering Opportunities at Fannie Mae (Associate to Management Levels) – (Flexible Hybrid)
How would you approach developing a forecasting model for mortgage loan performance?

To develop a forecasting model for mortgage loan performance, I would start by gathering historical loan performance data. Next, I would identify key variables influencing performance, such as economic indicators and borrower behaviors. I would then leverage statistical techniques and machine learning algorithms to build and validate the model, ensuring it accurately predicts future outcomes through rigorous testing.

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Can you explain a challenging quantitative problem you've solved in the past?

In my previous role, I encountered a complex issue with model risk assessment during our mortgage rate fluctuations. By applying advanced statistical techniques and conducting thorough sensitivity analyses, I identified critical variables causing inaccuracies. I implemented refinements, enhancing the model's predictive capability and ensuring compliance with regulatory standards.

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What programming languages are you proficient in and how have you used them in previous projects?

I am proficient in Python and R, using Python for data manipulation and algorithm development, while R has been instrumental in statistical analysis. In a recent project, I developed a predictive model for market trends using Python, employing various libraries for data visualization and statistical testing, which significantly improved our analytics framework.

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How do you ensure compliance with regulatory policies in your quantitative work?

To ensure compliance with regulatory policies, I closely follow the established guidelines such as FHFA directives and Basel standards. I integrate these regulations at each project stage, conduct regular audits, and collaborate with compliance teams to validate our methodologies, ultimately ensuring our models meet the necessary requirements.

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Describe your experience with stress testing in financial models.

I have extensive experience with stress testing, focusing on developing scenarios that reflect extreme market conditions. I utilize historical data and hypothetical situations to assess model responses, identify vulnerabilities, and ensure our risk management strategies are robust, ultimately aligning with Fannie Mae's compliance and risk policies.

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How do you approach teamwork in a cross-functional environment?

I believe in fostering open communication and collaboration in a cross-functional environment. I actively engage with team members from diverse backgrounds, ensure transparency in sharing insights, and align our goals. This approach has led to successful project outcomes and has strengthened relationships across different departments.

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What do you consider when designing quantitative models?

When designing quantitative models, I consider the model's purpose, the data quality, and the underlying assumptions. It's vital to ensure that the model is both flexible and robust, capable of adapting to new data while providing reliable forecasts. Additionally, I prioritize thorough documentation and validation processes to maintain accuracy and compliance.

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What techniques do you use to monitor model performance?

I utilize several techniques, including backtesting, sensitivity analysis, and performance metrics evaluation. By comparing predicted outcomes against actual results, I continuously refine the model. Regularly reviewing these metrics allows me to detect any discrepancies early and adjust parameters to maintain performance standards.

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How do you stay updated with advancements in quantitative finance?

To stay updated, I regularly read industry publications, attend conferences, and participate in webinars focused on quantitative finance and emerging technologies. I also engage in professional networks and forums, ensuring I am informed about best practices and innovations that can be applied to my work.

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What strategies would you implement to improve model coverage and performance?

To improve model coverage and performance, I would implement advanced statistical techniques, including machine learning algorithms. Ensuring inclusion of diverse datasets and continuous model validation through rigorous testing will enhance its accuracy. Additionally, I would solicit feedback from team members to identify blind spots and areas for improvement continuously.

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Fannie Mae’s mission is to facilitate equitable and sustainable access to homeownership and quality, affordable rental housing across America.

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Full-time, hybrid
DATE POSTED
March 16, 2025

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