Senior Quantitative Analytics: 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

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.