Quantitative Analytics Senior

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 Senior to be responsible for the development and execution of quantitative/analytic 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, thorough and practical solutions to an extensive range of demanding 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 align with model oversight and support model review for approval.
• Working under limited direction, independently determining and developing approach to solutions.

Qualifications:

• Doctorate degree (or Master’s degree with equivalent work experience) in quantitative finance, statistics, economics or a related quantitative field
• Coursework or work experience applying predictive modeling techniques from finance, statistics, mathematics, data science, and computer programming to large data sets. Qualifying coursework may include—but is not limited to—statistics, mathematical programming, optimization, machine learning, computational methods, design and analysis of algorithms, Bayesian methods, derivatives, and Monte Carlo methods
• Coursework or work experience writing statistical or optimization programs to develop models and algorithms. Programming languages may include—but are not limited to—SAS, Python, R, SQL, Java, and MATLAB
• PhD in Statistics, Math, Economics, Quantitative Finance or a related quantitative field; or Master degree with at least three years of related experience
• 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
• Strong knowledge of econometric models, tools and techniques
• Strong programming skills