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Position Overview:

Freddie Mac’s Investments & Capital Markets (I&CM) Division is seeking a Quantitative Analytics Tech Lead to join the Models & Analytics group to develop and enhance mortgage prepayment, default and severity models for portfolio management. The team is responsible for developing models and conducting quantitative analysis to support valuation and hedging of mortgage products.

Our Impact:

The Modeling and Analytics group in Freddie Mac's Investments and Capital Markets division develops financial and statistical models that are used for valuation and risk analytics purposes.

Your Impact:

Freddie Mac’s Investments & Capital Markets (I&CM) Division is seeking a Quantitative Analytics Tech Lead to join the Models & Analytics group to develop and enhance mortgage prepayment, default and severity models for portfolio management. The team is responsible for developing models and conducting quantitative analysis to support valuation and hedging of mortgage products.

Our Impact:

The Modeling and Analytics group in Freddie Mac's Investments and Capital Markets division develops financial and statistical models that are used for valuation and risk analytics purposes.

Your Impact:

The successful candidate will contribute to the development of mortgage valuation model and conduct portfolio analysis to support trading and hedging activities.

Your Work Falls Into Four Primary Categories:

Model Development and Research

• Developing mortgage prepayment, default and severity models that assess market risk of mortgages, mortgage backed securities, and senior-sub structured products
• Applying statistical modeling and big data analytics tools and developing innovative solutions for forecasting mortgage borrower behavior
• Conducting research on industry models, market conditions, and regulatory environment.

Portfolio Analysis

• Developing and enhancing valuation processes and risk metrics for our retained portfolio of mortgage products.
• Conducting sensitivity analysis and impact assessment for model updates and changes in model inputs.

Model Governance

• Preparing model documentation and conducting thorough model validation tests.
• Developing on-going performance monitoring and threshold methodology.

Business Support

• Providing analytics support for trading and hedging activities.
• Working under limited direction, independently determining and developing approach to solutions.

Qualifications:

• Doctorate degree plus 3 years of working experience (or Master's degree with equivalent 5 years of working experience) in statistics, data science or a related quantitative field.

• 5+ years of relevant experience applying predictive modeling techniques or data analytics to large datasets is preferred.

• Post-graduate work experience in mortgage valuation and statistical modeling

• Programming skills in one or more of Python, R, SAS or related languages

• Exceptional quantitative, empirical analysis, and research skills

• Experience working with large data sets and relational database

• Experience in statistical model development and implementation is preferred

Keys to Success in this Role:

• Exceptional quantitative, empirical analysis, and research skills
• Strong knowledge of survival analysis and mortgage valuation
• Strong programming skills and knowledge in big data analytics such as Apache Spark and AWS cloud computing

Top 3 Personal Competencies to Possess:

• Drive for Execution – Execute effectively with a clear direction and objective, good ownership
• Partnership – Build trust and strong partnerships within the team; good team player
• Leadership – Set and execute upon a clear vision and goals; good communication, interpersonal, and leadership 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 accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

A safe and secure environment is critical to Freddie Mac’s business. This includes employee commitment to our acceptable use policy, applying a vigilance-first approach to work, supporting regulatory mandates, and using best practices to protect Freddie Mac from potential threats and risk. Employees exercise this responsibility by executing against policies and procedures and adhering to privacy & security obligations as required via training programs.

CA Applicants: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.

Notice to External Search Firms: Freddie Mac partners with BountyJobs for contingency search business through outside firms. Resumes received outside the BountyJobs system will be considered unsolicited and Freddie Mac will not be obligated to pay a placement fee. If interested in learning more, please visit www.BountyJobs.com and register with our referral code: MAC.

Time-type:Full time

FLSA Status:Exempt

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 $144,000 - $216,000 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.