Freddie Mac

Developing mortgage prepayment, default and severity models that assess market and credit risk of mortgage backed securities, and senior-sub structured products, as well as whole loans. Doctorate degree (or Master's degree with equivalent work experience) in quantitative finance, statistics or a related quantitative field.. MS in Economics, Quantitative Finance, Statistics or a directly related quantitative field with at least 3 years of related post-graduate work experience in mortgage valuation and statistical modeling. Programming languages may include-but are not limited to-Python, R, SQL, Java, SAS, and MATLAB.. Programming skills in one or more of R, Python, SQL, Java, SAS or related languages

quantitative

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.
<h3>Position Overview</h3>
At Freddie Mac, you will do meaningful 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.
Freddie Mac's Investments & Capital Markets Division is seeking a Quantitative Analytics Senior to join the Models & Analytics group to develop and enhance mortgage prepayment, default, severity and MSR models for portfolio management. The team is responsible for developing models and conducting quantitative analysis to support valuation and hedging of mortgage products.
<h3>Our Impact</h3>
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.
<h3>Your Impact</h3>
Model Development and research
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Developing mortgage prepayment, default and severity models that assess market and credit risk of mortgage backed securities, and senior-sub structured products, as well as whole loans
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Applying statistical modeling and developing innovative solutions for forecasting mortgage borrower behavior
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Conducting research on industry models, market conditions, and regulatory environment.
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Portfolio analysis
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Developing and enhancing valuation processes and risk metrics for our retained portfolio of mortgage products.
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Conducting sensitivity analysis and impact assessment for model updates and changes in model inputs.
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Model governance
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Preparing model documentation and conducting thorough model validation tests.
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Developing on-going performance monitoring and threshold methodology.
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Business support
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Providing analytics support for trading and hedging activities.
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Working under limited direction, independently determining and developing approach to solutions.
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<h3>Qualifications</h3>
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Doctorate degree (or Master's degree with equivalent work experience) in quantitative finance, statistics or a related quantitative field.
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MS in Economics, Quantitative Finance, Statistics or a directly related quantitative field with at least 3 years of related post-graduate work experience in mortgage valuation and statistical modeling
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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/modeling.
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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, Java, SAS, and MATLAB.
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Demonstrated knowledge of Econometrics modeling techniques.
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Demonstrated knowledge of Financial asset valuation and risk management.
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Outstanding quantitative, empirical analysis, and research skills.
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Programming skills in one or more of R, Python, SQL, Java, SAS or related languages
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Experience with mortgage modeling and analytics is preferred but not required.
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<h3>Keys to Success in this Role</h3>
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Keen willingness and strong ability to learn new domain knowledges and skills
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Strong analytical skills with good understanding of data
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Superior technical and programming skills (stats, math, Python, R, etc.).
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Good verbal and written communication skill
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Current Freddie Mac employees please apply through the internal career site.
Today, Freddie Mac makes home possible for one in four home borrowers and is one of the largest sources of financing for multifamily housing. Join our smart, creative and dedicated team and you'll do important work for the housing finance system and make a difference in the lives of others.
We are an equal opportunity employer and value diversity and inclusion at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by applicable law. We will ensure that individuals with differing abilities 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.
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 $118,000 - $178,000 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.

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