Quantitative Analytics Senior

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.

As a Data Scientist on the Collateral Modeling and Analytics team at Freddie Mac, you will join a group of skilled professionals who use data science to solve important business problems. You will apply statistical and machine learning techniques to build tools that will be used daily to make decisions about the collateral underlying the mortgages in Freddie Mac’s portfolio. You will make efficient use of distributed computing technologies and state of art modeling algorithms with the latest structured and unstructured big data available.

Full time

Exempt

Our team build tools that will be used daily to make decisions about the collateral underlying the mortgages in Freddie Mac’s portfolio and help the company to make intelligent business decisions for risk management.

• Developing analytical methods and models that assess the collateral risk of new and existing financial and mortgage products.
• 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, and 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 align with model oversight and support model review for approval.
• Working under limited direction, independently resolving problems, and developing approach to solutions.

• Doctorate degree, or Master degree with 3 years of equivalent work experience, in statistics, computer science, statistics, economics or a related quantitative field.
• Coursework or work experience in 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, advanced statistics, mathematical programming, optimization, machine learning, computational methods, design and analysis of algorithms, Bayesian methods, derivatives, or Monte Carlo methods.
• Coursework or work experience in writing statistical or optimization programs to develop models and algorithms. Programming languages may include, but are not limited to, Python, R, SAS, SQL, Java, or MATLAB.
• Experience in working with large data sets and relational database.
• Experience in statistical model development and implementation is preferred.
• Experience with software development and system setup for model application is preferred.
• Experience in machine learning libraries such Scikit-learn, Tensor Flow, PyTorch, and Dask is preferred.
• Experience with advanced algorithms, ensemble method, text mining, and image analytics is a plus.
• Demonstrated knowledge of AI tools and technologies, with a strong commitment to continuous learning and staying up-to-date with advancements in artificial intelligence

• Strong oral and written communication skills with ability to succinctly describe complex technical scenarios in simple and easily-understood terms.
• Solid oral and written communication…