Quantitative Analytics Senior
About The Position
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. Join an organization where your work contributes to a greater purpose. Position Overview: 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 Impact: 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. Your Impact: 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.
Requirements
- 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
Responsibilities
- 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.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
Ph.D. or professional degree
Number of Employees
5,001-10,000 employees
