Quantitative Analytics Senior

Freddie Mac’s Investments & Capital Markets Division is currently seeking a Quantitative Analytics Senior to be responsible for the creation, development, and execution of analytic models used to value Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD) of various types of financial institutions., * Design, code and maintain consistent counterparty credit risk models (PD/LGD/EAD).

• These models must incorporate best practices while simultaneously accounting for the unique characteristics and risks of each financial institution.
• Collaborate with the Counterparty Credit Risk Management (CCRM) Team to gain in-depth understanding of various types of financial institutions (e.g. Mortgage Banks, Depository Institutions, 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.
• On a quarterly basis, design and run Performance Monitoring Reports, respond to questions from business users, model validation, audit, and model risk oversight.
• Periodically review and understand changes of relevant corporate policies, standards and procedures and act as a liaison in associated model implementation validation.
• Own other standard parts of modeling job such as understanding and complying with all official model controls related to models owned by the team.
• Collaborate with the 1st line Model Governance team in I&CM to ensure that counterparty models adhere to Freddie Mac’s model governance standards.
• Proactively partner with teammates and users to co-develop unique approaches and facilitate ideas.

The candidate should be self-motivated, have a strong computational background, and effective communication skills. Under the Models & Analytics team, the candidate will support models primarily utilized by Freddie Mac’s Counterparty Credit Risk Management Team. The key focus is on credit risk scorecard modeling, but the tasks may also include LGD and EAD models. The position encourages continued learning and development across other modeling areas, including market risk capital, operational loss forecast, prepayment and default, and rates and derivatives ., * PhD in economics, finance, statistics, or a related quantitative discipline, or Master’s degree with 3+ years of relevant experience.

• Demonstrated knowledge of Econometrics modeling techniques.

• Outstanding quantitative, empirical analysis, and research skills
• 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-econometrics, statistics, mathematical programming, optimization, computational methods, design and analysis of algorithms, Bayesian methods, derivatives, and Monte Carlo methods/modeling.
• Coursework or work experience writing statistical and/or optimization programs to develop models and algorithms. Programming languages may include–but are not limited to–Python, R, SQL, and MATLAB.
• Strong Programming skills is a must! Python and SQL are most frequently used; other useful languages and software available in the company include Java, SAS, MATLAB, C.
• Experience with mortgage modeling and analytics preferred., * Strong programming skills
• Strong technical skills (stats, math)
• Strong analytical skills with orientation to detail
• Good verbal and written communication skills

Freddie Mac offers a comprehensive total rewards package to include competitive compensation and market-leading benefit programs. Information on these benefit programs is available on our Careers site.

This position has an annualized market-based salary range of $126,000 - $190,000 and is eligible to participate in the annual incentive program. The final salary offered will generally fall within this range and is dependent on various factors including but not limited to the responsibilities of the position, experience, skill set, internal pay equity and other relevant qualifications of the applicant.