A leading consulting firm is looking for a Credit Risk Modeler for remote, project-based opportunities. The role involves performing validations of credit decisioning models and demands a solid understanding of predictive accuracy. Candidates should have at least 5 years of experience in the financial services industry, along with strong Python and R programming skills. An undergraduate degree in a quantitative discipline is required. Treliant offers competitive compensation and a flexible benefits package.
Qualifications
5+ years of credit risk model validation work experience within the financial services industry.
Experience using Machine Learning packages and evaluating Machine Learning algorithms in consumer lending.
Understanding of CCAR and DFAST is required.
Responsibilities
Perform thorough model validation of credit decisioning and related consumer lending models.
Evaluate predictive accuracy of model assumptions against actual performance.
Document results in a concisely written report.
Skills
Python
R programming
Model validation
Machine Learning
Education
Undergraduate degree in a quantitative discipline
Advanced degree
Tools
SAS
Stata
Job description
A leading consulting firm is looking for a Credit Risk Modeler for remote, project-based opportunities. The role involves performing validations of credit decisioning models and demands a solid understanding of predictive accuracy. Candidates should have at least 5 years of experience in the financial services industry, along with strong Python and R programming skills. An undergraduate degree in a quantitative discipline is required. Treliant offers competitive compensation and a flexible benefits package.