ERM Quantitative Analytics Director (ML)

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:

Responsible for the critical review and independent testing of quantitative/analytic models and in support of business, risk decisions, and financial reporting. Apply now and learn about our excellent benefits and why there's #MoreAtFreddieMac!

Our Impact:

The team is primarily responsible for validation of market risk models

Your Impact:

• Reviewing analytical methods and quantitative models for new and existing financial and mortgage products/portfolio.
• Providing resolutions to an extensive range of complicated problems; solutions are innovative, thorough, and practicable
• Acts as the Model Risk lead for model testing and validation
• Developing validation reports based on rigorous theoretical and analytical reviews of models.
• Acting as an advisor and leader for subordinates to meet schedules and/or resolve technical problems as well as developing and coordinating performance requirements.
• Managing the coordination of the activities of a section or department. Often must lead joint effort among with members of different team.
• Manage validation of credit decisioning models. Participate in ERM's credit strategy review/challenge process.
• Manage validation of models built using modern ML/AI techniques (Neural networks, Random Forest, and various boosting algorithms).

• MS in Economics, Finance, Statistics, Engineering, MBA with a concentration in Finance, Operational research, or a directly related quantitative field with at least 10 years of post-graduate work experience in quantitative analytics or modeling
• Programming experience with a good level of knowledge of at least one: Matlab, STATA, Python, C++, SAS, R
• Deeply knowledgeable of regression models, stochastic process modeling, Monte-Carlo simulation, Optimization and/or other econometric and statistical techniques such as survival, proportional hazards, etc.
• Knowledge of AIML techniques such as neural networks, random forest, XGBoost and similar algorithms
• Experience in the financial sector preferred
• Ability to work across teams and with diverse organizations of modeling and risk professionals in an effective and efficient manner.

• Intellectual agility and interpersonal flexibility
• Strong consultation and communication skills
• Ability to work with and collaborate across diverse teams and silos
• Deep intellectual curiosity to explore new methods and learn new techniques outside one's own acumen
• Ability to apply analytical results to help advise on strategy and business direction
• Ability to discern between observations and findings, and between what are issues of modeling opinion versus true model limitations and performance issues that present risk to the company
• Superior written and verbal communication
• Seek and Embrace Change - Continuously improve work processes rather than accepting the status quo
• Outstanding ability to lead and influence within and beyond the ERM organization.