Quantitative Analytics Professional A
Listed on 2026-08-10
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Finance & Banking
Data Scientist, Mathematics -
IT/Tech
Data Scientist, Mathematics
Job Title
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.
Job DescriptionDevelop strategies to analyze and interpret output of models or analytic applications, which assess things such as relative risks of each product within the portfolio. Plan, execute, and document analysis of complex financial models. Provide portfolio risk assessments based on findings. Provide modeling and analytical assistance to a line of business or product area, functioning as day-to-day technical expert. Evaluate and manage risks associated with the company's models, including models of defaults, security valuation, prepayments, loan scoring, and others.
Provide innovative, thorough, and practical solutions to an extensive range of demanding problems, including analyses of relative value. Full use and application of standard principles, theories, concepts, and techniques. Primarily intra-organizational with occasional interorganizational and external customer contacts on routine matters. Position may be eligible for part-time telecommuting.
Master's degree or foreign equivalent in statistics, mathematics, economics, finance, or closely related quantitative field. Must have demonstrated knowledge of the following skills:
- Using and applying predictive modeling techniques from finance, statistics, mathematics, data science, and computer programming to large data sets.
- Statistics, mathematical programming, optimization, machine learning, computational methods, design and analysis of algorithms, Bayesian methods, derivatives, and Monte Carlo methods/modeling.
- Writing statistical and/or optimization programs to develop models and algorithms.
- Programming languages, such as Python, R, SQL, Java, SAS, or MATLAB.
Employer will accept any combination of education that has been evaluated by a professional credentials evaluation service to be the equivalent of a U.S. degree.
Knowledge may be demonstrated through education, training, and/or experience.
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