Quantitative Analytics Senior - House Price Index Modeling

Freddie Mac•McLean, VA

About The Position

Freddie Mac’s Single-Family Division is seeking a Quantitative Analytics Senior to develop and execute statistical models and applications supporting business and risk decisions as a member of the House Price Index Modeling Team. This role is crucial for advancing Freddie Mac’s mission by developing robust and interpretable models for tracking house price appreciation. The team develops robust, scalable models that support the Single-Family business by enabling critical, data-driven risk decisions. The team is responsible for developing house price index models for Freddie Mac. As a Data Scientist, you will join a group of skilled professionals who use data science to solve important business problems.

Requirements

Doctorate degree, or Master degree with 3 years of equivalent work 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, or 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, or Monte Carlo methods
Coursework or work experience writing statistical or optimization programs to develop models and algorithms. Programming languages may include—but are not limited to—SAS, Python, R, SQL, and MATLAB
Experience working with large data sets and relational database

Nice To Haves

Experience in statistical model development and implementation is preferred
Experience with software development and system setup for model application is preferred

Responsibilities

Developing analytical methods and models about the collateral underlying the mortgages in Freddie Mac's portfolio.
Conducting research on enhancements to the existing models, and applying industry standard processes and techniques to meet various business needs.
Providing innovative, detailed and practical solutions to an extensive range of demanding and complicated problems.
Implementing statistical models in efficient software languages, coding model prototypes for specification and test cases, modifying source codes in the existing application.
Coordinating the testing through the model implementation, conducting back tests to monitor the model performance, and performing economic tests and stress tests to validate the model forecast results.
Providing modeling and analytical support to a line of business or product area, functioning as day-to-day technical specialist.
Preparing documentation for the technical analytics and rationale through the model development to comply with model oversight and support model review for approval.
Working under limited direction, independently resolving and developing approach to solutions.