Quantitative Analytics Tech Lead - Economic Modeling

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

At Freddie Mac, you will do important work to build a better housing finance system and you’ll be part of a team helping to make homeownership and rental housing more accessible and affordable across the nation.

Position Overview:

Freddie Mac’s Single-Family Division is currently seeking a Quantitative Analytics Technical Lead 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 Default Costing Model Team. Apply now and learn why there’s #MoreAtFreddieMac!

**This position can be performed currently from a remote location in the U.S. but will require presence in a Freddie Mac office in the future.***

Our Impact:

Our team is responsible for the development and analytic support of the Default Costing model (Forecast of Credit Risk and Severity), supports 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 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 the 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.

Qualifications:

• PhD in Statistics, Math, Economics, Computer Science or a related quantitative field with at least 3 years of related post-graduate work experience; or Master degree with at least 6 years of related experience
• At least three years of experience in model development including logistic regression
• Strong programming skills in SAS, SQL and Unix.
• Experience with programming language such as Python, 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 models, transition models, loss forecasting and stress testing
• Experience in data science, machine learning and related technologies

Keys to Success in this Role:

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