Credit Model Specialist

Treliant LLC•Remote,

1d•$75 - $150•Remote

About The Position

Treliant is an essential consulting firm serving banks, mortgage originators and servicers, fintechs, and other companies providing financial services globally. We are led by practitioners from the industry and the regulatory community who bring deep domain knowledge to help our clients drive business change and address the most pressing compliance, regulatory, and operational challenges. We provide data-driven, technology-enabled consulting, implementation, staffing, and managed services solutions to the regulatory compliance, risk, credit, financial crimes, and capital markets functions of our clients. Founded in 2005, Treliant is headquartered in Washington, DC, with offices across the United States, Europe, and Asia. Treliant is committed to fostering a diverse, equitable and inclusive environment that values and embraces all races, religions, ages, abilities, genders, sexual orientations, ethnicities, languages, nationalities, political parties, socioeconomic groups and other characteristics that inform an individual's worldview, experiences and system of beliefs (“the principles”). We believe in championing every voice and ensuring everyone’s full potential. Treliant is looking for Credit Risk Modelers for remote, project-based opportunities.

Requirements

Undergraduate degree in a quantitative discipline (i.e. statistics, econometrics, engineering).
5+ years of credit risk model validation work experience within the financial services industry.
Strong Python and R programming skills.
Experience using Machine Learning packages and evaluating Machine Learning algorithms in consumer lending/leasing or similar businesses.
Understanding of CCAR and DFAST.
Comfort working in a fast-paced and deadline-driven consulting environment.
Applicants must be able to work in the United States without requiring sponsorship.

Nice To Haves

Advanced degree a plus.
Experience using SAS and/or Stata software packages a plus.

Responsibilities

Perform thorough model validation of credit decisioning and related consumer lending models.
Rigorously evaluate predictive accuracy of model assumptions against actual performance and requirements.
Document results in a concisely written report.
Clearly present work to the project lead.