5-7 years of experience in credit risk model development (PD, LGD, EAD, ALLL).
Strong programming skills in Python and PySpark.
Degree in Statistics, Mathematics, Engineering, Financial Engineering, or a related field.
Proven practical experience with rating models in the financial or banking sector.
Solid grounding in quantitative and statistical methodologies.
Responsibilities
Develop and enhance credit risk models using Python and PySpark.
Collaborate with quantitative teams on model design and validation.
Conduct statistical analysis and model calibration.
Translate business and regulatory requirements into model specifications.
Prepare documentation for internal and external model reviews.
Benefits
Opportunity to work on cutting-edge credit risk models.
Collaborative environment with quantitative and business teams.
Exposure to regulatory framework development.
Potential for professional growth within a well-established financial institution.
On-site work in New York City, a major financial hub.
Full Job Description
Job Title: Credit Model Developer Location: New York, USA/On-Site Interview Process: 2 Rounds - 1 Virtual & 1 Face-to-Face
Job Summary: We are seeking a skilled Credit Model Developer with strong expertise in Python and PySpark, coupled with a solid statistical or quantitative background. The ideal candidate will have experience in credit risk model development (PD, LGD, EAD, ALLL) and a deep understanding of rating models used in financial institutions.
Key Responsibilities: Develop, enhance, and implement credit risk models (PD, LGD, EAD, ALLL) using Python and PySpark. Work closely with quantitative teams to design, test, and validate model frameworks. Perform statistical analysis, model calibration, and performance monitoring. Collaborate with business and risk teams to translate regulatory and business requirements into model specifications. Prepare documentation and support internal/external model reviews.
Required Skills & Qualifications: Strong programming skills: Python and PySpark (hands-on experience required). Quantitative / Statistical background - degree in Statistics, Mathematics, Engineering, Financial Engineering, or related field. Proven experience in credit risk model development (PD, LGD, EAD, ALLL). Experience working on rating models within financial or banking domains. Note: This role focuses on model development - model validators are not required.
Nice to Have: Experience with regulatory model frameworks and governance processes. Familiarity with large-scale data environments and distributed computing.
