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    Quantitative Analytics Professional - McLean, United States - Freddie Mac

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    Full time
    Description
    JOB DESCRIPTION

    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.

    Position Overview:

    Are you looking for an opportunity to conduct meaningful empirical research and analytics? Do you want to work with a team that provides insights to stakeholders to help drive decisions and help achieve company objectives?

    We are looking for a team member who is ready to apply their analytic skills to research that matters for Freddie Mac's mission

    Our Impact:

    The Housing Insights and Solutions team in Freddie Mac's Single-Family Mission and Community Engagement Division offers research and technical expertise on housing data and policy issues with a focus on access to credit and underserved communities. We conduct and present research and analytics to provide insights for the affordable housing goals, duty to serve underserved markets, and business decisions in pursuit of our community mission.

    Your Impact:

  • Support Housing Insights and Solutions team through data preparation, complex data and statistical analysis, and model output assessment.
  • Design and implement processes and analytical tools to proactively support our community mission.
  • Support research and analytics related to the affordable housing goals, duty to serve underserved markets, equitable access to credit, and expanding sustainable homeownership.
  • Write memos or presentation materials summarizing results of analyses performed.
  • Write programs to clean and analyze large volumes of structured and unstructured data.
  • Research data tools and sources to develop efficient processes to retrieve and use relevant information.
  • Refresh information, tools, processes and analytical systems with modifications as needed.
  • Prepare and maintain documentation of models, processes and programs in use.
  • Maintain working relationships with other departments and divisions.
  • Qualifications:

  • Master's degree or equivalent experience in quantitative finance, statistics, Economics or a related quantitative field.
  • Coursework or work experience applying predictive modeling techniques from finance, statistics, mathematics, data science, and computer programming to large data sets.
  • 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.
  • Proficiency with Microsoft Excel and PowerPoint.
  • Keys to Success in this Role:

  • Ability to apply an analytical approach to understand problems and propose actionable solutions supporting strategic business decisions
  • Exceptional quantitative, empirical analysis, and research skills
  • Strong oral and written communication skills with ability to succinctly describe complex technical scenarios and analysis
  • 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.



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