Quantitative Analytics Senior - Data Scientist (Hybrid - 3 Days in Office)

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 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.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.The successful candidate will contribute to the development of prepayment model and conduct portfolio analysis to support trading and hedging activities.Developing mortgage prepayment, default and severity models that assess market risk of mortgage backed securities, CMOs, and senior-sub structured productsApplying statistical modeling and big data analytics tools and developing innovative solutions for forecasting mortgage borrower behaviorConducting research on industry models, market conditions, and regulatory environment.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.Preparing model documentation and conducting thorough model validation tests.Developing ongoing performance monitoring and threshold methodology.Providing analytics support for trading and hedging activities.Working under limited direction, independently determining and developing approach to solutions.Qualifications:

Doctorate degree (or Master's degree with equivalent work experience) in statistics, data science or a related quantitative field.Coursework or work experience applying predictive modeling techniques from data science, statistics, machine learning, and econometrics to large data sets. Qualifying coursework may include—but is not limited to—data science, statistics, machine learning, optimization, numerical analysis, scientific programming, computational methods, supervised learning, unsupervised learning, text mining, and image analysis.Coursework or work experience writing computer programs to implement data science pipelines and predictive algorithms. Programming languages may include—but are not limited to—Python, R, SQL, Java, SAS, and MATLAB.Coursework or work experience using technologies for manipulating structured and unstructured big data. Big data technologies may include—but are not limited to—Hadoop, Hive, Pig, Spark, relational databases, and NoSQL.OR MS in Economics, Finance, Statistics or a directly related quantitative field with at least 3 years of related post-graduate work experience in mortgage valuation and statistical modelingProgramming skills in one or more of SAS, R, Python or related languagesExceptional quantitative, empirical analysis, and research skillsExperience with SQL and working with relational databasesKeys to Success in this Role:

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

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