Quantitative Analytics Senior (Credit Risk Modeling)

Freddie Mac; McLean (VA); On-site; USD 126,000 - 190,000; Full time

Job summary

Freddie Mac is seeking a Quantitative Analytics Senior to develop and execute statistical models for credit risk decisions within the Credit Risk Modeling Team. You will apply econometric, machine learning, and statistical methods to forecast mortgage portfolio risk and support business strategy.

Key responsibilities include designing analytical methods, validating models, performing stress tests, and documenting rationale for oversight.

Qualifications

• PhD in Economics, Statistics, Math, CS or related field, or Master's with 3+ years post-graduate experience.
• Strong programming skills in Python, SQL, SAS, and Unix.
• Experience with large data sets and relational databases.
• Experience with mortgage or consumer credit risk models and loss forecasting.

Responsibilities

• Develop analytical methods and models assessing credit risk of new and existing products.
• Provide innovative solutions to fast-paced, complex problems.
• Develop and validate loss forecasting models and stress tests.
• Coordinate testing through model implementation and back tests.
• Provide modeling support to business areas as day-to-day technical specialist.
• Prepare documentation to comply with model oversight and reviews.
• Work independently to determine approaches to solutions.

Skills

Quantitative analysis

Empirical research

Modeling expertise

Education

PhD in Economics/Statistics/Math/CS or related field

Master's degree with 3+ years post-graduate experience

Tools

Python

SQL

SAS

Unix

R

VBA

Java

C++

Job description

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.

Position Overview:

Freddie Mac’s Single-Family Division is currently seeking a Quantitative Analytics Senior to be responsible for the development and execution of statistical models and applications in support of business and risk decisions as a member of the Credit Risk Modeling Team.

Our Impact:

Our team is responsible for the development and analytic support of credit risk models, supports the single-Family business for risk decisions. We apply econometric, machine learning and statistical modeling to understand business problems and produce credit risk forecast for the mortgage portfolio.

Your Impact:

• Developing analytical methods and models that assess the credit risk of new and existing financial and mortgage products.

• Providing innovative, detailed and practical solutions to an extensive range of fast paced and complicated problems.

• Developing and validating loss forecasting models, conducting research on improvements to the existing models, and applying industry standard methodologies and techniques to meet various business needs.

• 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 determining and developing approach to solutions.

Qualifications:

• PhD in Economics, Statistics, Math, Computer Science or a related quantitative field; or Master's degree with at least 3 years of related post-graduate work experience

• Strong programming skills in Python, SQL, SAS and Unix

• Experience with programming language such as R, VBA, Java or C++

• Experience working with large data sets and relational database

• Experience working with mortgage or consumer credit risk models, prepayment models and severity models

• Experience with competing-risk hazard models, transition models, loss forecasting and stress testing

• Experience in data science, machine learning and related technologies

Keys to Success in this Role:

• Outstanding quantitative, empirical analysis, and research skills

• Solid understanding of econometric models, tools and techniques

• Strong programming skills

We consider all applicants for all positions without regard to gender, race, color, religion, national origin, age, marital status, veteran status, sexual orientation, gender identity/expression, physical and mental disability, pregnancy, ethnicity, genetic information or any other protected categories under applicable federal, state or local laws. We will ensure that individuals 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.

A safe and secure environment is critical to Freddie Mac’s business. This includes employee commitment to our acceptable use policy, applying a vigilance-first approach to work, supporting regulatory mandates, and using best practices to protect Freddie Mac from potential threats and risk. Employees exercise this responsibility by executing against policies and procedures and adhering to privacy & security obligations as required via training programs.

CA Applicants: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.

Time-type:Full timeFLSA Status:Exempt

Freddie Mac offers a comprehensive total rewards package to include competitive compensation and market-leading benefit programs. Information on these benefit programs is available on our Careers site.

This position has an annualized market-based salary range of $126,000 - $190,000 and is eligible to participate in the annual incentive program. The final salary offered will generally fall within this range and is dependent on various factors including but not limited to the responsibilities of the position, experience, skill set, internal pay equity and other relevant qualifications of the applicant.