Quantitative Analytics Senior

At Freddie Mac, our mission of Making Home Possible is what motivates us, and it’s at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Continue your career journey where your work contributes to a greater purpose.

Freddie Mac’s Single-Family Division is currently seeking a Quantitative Analytics Senior to be responsible for the development and execution of statistical models and applications in support of business and risk decisions as a member of the Credit Risk Model Team.

Our team is responsible for the development and analytic support of credit risk models such as credit event state transition model supporting the single-Family business for risk decisions. We apply econometric, machine learning and statistical modeling to understand business problems and produce credit risk forecast for the mortgage portfolio.

• Developing analytical methods and models that assess the credit risk of new and existing financial and mortgage products.
• Providing innovative, detailed and practical solutions to an extensive range of fast-paced and complicated problems.
• Developing and validating delinquency and loss forecasting models, conducting research on improvements to the existing models, and applying industry standard methodologies and techniques to meet various business needs.
• Coordinating the testing through the model implementation, conducting back tests to monitor the model performance, and performing economic tests and stress tests to validate the model forecast results.
• Providing modeling and analytical support to a line of business or product area, functioning as day-to-day technical specialist.
• Preparing documentation for technical analytics and rationale through the model development to comply with model oversight and support model review for approval.
• Working under limited direction, independently determining and developing approach to solutions.

• PhD in Statistics, Math, Economics, Computer Science or a related Quantitative Computational Finance field; or Master degree in similar majors with at least 3 years of related experience in model development including logistic regression with large data sets.
• Strong programming skills in SAS, Python, SQL and Unix.
• Experience with programming languages such as R, VBA, Java or C++
• Experience working with large data sets and relational database
• Experience working with mortgage or consumer credit risk models, prepayment models and severity models
• Experience with competing-risk hazard / transition modeling, and loss forecasting and stress testing processes.
• Experience in data science, machine learning and related technologies

• Outstanding quantitative, empirical analysis, and research skills
• Solid understanding of econometric models, tools and techniques
• Strong programming skills

We consider all applicants for all positions without regard to gender, race, color, religion, national origin, age, marital status, veteran status, sexual orientation, gender identity/expression, physical and mental disability, pregnancy, ethnicity, genetic information or any other protected categories under applicable federal, state or local laws. We will ensure that individuals are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment.

Please contact us to request accommodation.

Freddie Mac offers a comprehensive total rewards package to include competitive compensation and market-leading benefit programs. Information on these benefit programs is available on our Careers site.

This position has an annualized market-based salary range of $125,000 - $187,000 and is eligible to participate in the annual incentive program. The final salary offered will generally fall within this range and is dependent on various factors including but not limited to the responsibilities of the position, experience, skill set, internal pay equity and other relevant qualifications of the applicant.