Quantitative Analytics Professional at Freddie Mac in McLean, VA

  • Company: Freddie Mac
  • Location: McLean, VA
  • Salary: $105K – $157K
  • Job type: full time
  • Workplace: onsite
  • Posted: 2026-10-29

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Job description

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 Investments & Capital Markets Division is currently seeking a Quantitative Analytics Professional within the Models & Analytics team to be responsible for the creation, development, and execution of analytic models in support of Counterparty Risk Management. The key focus is on exposure measurement driven by market risk factors for various products and counterparty types, but the tasks may also include counterparty credit risk exposure, LGD, and credit rating models. The position encourages continued learning and development across other modeling areas, such as market risk capital, operational loss forecast, prepayment and default, and rates and derivatives. Our Impact: Key focus of this job is the design, development, and implementation of counterparty risk models for a variety of financial institutions, with primary focus on Exposure at Default models. These models support multiple corporate and divisional objectives by providing key inputs into counterparty credit risk management, both at individual counterparty and portfolio levels. Your Impact: Design, code and maintain consistent counterparty risk models (EAD/PD/LGD). Incorporate best practices while simultaneously accounting for the unique characteristics and risks of each financial institution. Collaborate with the Counterparty Credit Risk Management (CCRM) to gain in-depth understanding of various types of financial products (e.g. MBS, CMO, ARM, Whole Loans, Credit Risk Transfer, Insurers) in order to appropriately model unique associated risks Design and code model enhancements to address agreed-upon actions (AUAs) in response to findings from model reviewers, internal auditors, and regulatory examiners Design and produce Performance Monitoring Reports on a regular cadence, respond to inquiries from various stakeholders Periodically review and understand changes in relevant corporate policies, standards and procedures and act as a liaison in associated model implementation validation Understand and comply with all model controls related to models owned by the team Collaborate with the Divisional Model Governance team to ensure compliance with model governance standards Proactively partner with teammates and users to facilitate ideas and keep improving models Qualifications: Master's Degree in quantitative finance, statistics or a related quantitative field Qualifying coursework may include – but not limited to — econometrics, statistics, mathematical programming, optimization, computational methods, simulation, mortgage-backed securities, derivatives pricing, fixed income and term structure of interest rates Must have coursework or work experience developing and implementing financial models, with demonstrable knowledge in quantitative modeling and statistical analysis Experience with market risk and mortgage-related modeling and analytics strongly preferred Must have strong programming skills in Python and SQL. Familiarity with other languages such as Java, C++, MATLAB, SAS useful. Keys to Success in this Role: Strong programming skills Strong technical skills Strong analytical skills with orientation to detail Excellent verbal and written communication skills Current Freddie Mac employees please apply through the internal career site. 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 accommoda

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