Quantitative Analytics Senior - Economic/Policy Research

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

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? Do you want to work with a team that provides insights to partners 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! Apply now and learn why there’s #MoreAtFreddieMac!

**This position can be performed currently from a remote location in the U.S. but will require presence in a Freddie Mac office in the future.**

Our Impact:

Our team 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. We provide thought leadership by publishing and socializing research to academic audiences and industry partners.

Your Impact:

• Prepare and present analytics related to the affordable housing goals, duty to serve underserved markets, and access to credit.
• Plan, execute, and prepare written and oral presentations for research, including to identify opportunities for low- to moderate-income consumers and underserved communities
• Support Housing Insights and Solutions team through data preparation, complex data and statistical analysis, and model output assessment to support and drive business strategies and objectives.
• Provide innovative, thorough and practical solutions to an extensive range of demanding and complicated business problems.
• Collaborate with other areas of the company to support affordable and access to credit strategies.
• Work under limited direction, independently determining and developing approaches to solutions.

Qualifications:

• Doctorate degree (or master's degree with equivalent work experience) in economics, statistics 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. 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.
• 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.

Keys to Success in this Role:

• Exceptional quantitative, empirical analysis, and research skills
• Knowledge of statistical, econometric, and machine learning techniques
• Good communication, interpersonal, and leadership skills