Cognitud - Credit Risk Modeler

We are seeking a skilled and detail-oriented Credit Risk Modeler with hands-on expertise in SAS to support the development, validation, and implementation of credit risk models.

The ideal candidate will have a strong quantitative background, experience working with large financial datasets, and the ability to create models that support credit decisioning, portfolio risk assessment, and regulatory compliance.

Key Responsibilities

- Develop, implement, and validate credit risk models for PD, LGD, EAD, and scorecards using SAS.

- Analyze portfolio data to identify risk patterns and support credit risk segmentation and strategy design.

- Work with cross-functional teams (risk, finance, analytics, regulatory) to ensure models align with business needs and regulatory expectations.

- Perform statistical analysis, data cleaning, transformation, and variable selection using SAS tools.

- Maintain model documentation, coding standards, and audit trail in line with internal policies and external regulations (e.g., IFRS 9, Basel III).

- Support periodic model monitoring, calibration, back-testing, and performance tracking.

- Present model results and insights to senior stakeholders with clear communication of assumptions, methodology, and limitations.

Required Skills and Qualifications

- Minimum of 3 years of experience in credit risk modeling, preferably in a banking, NBFC, or financial services environment.

- Strong hands-on expertise in SAS/Base SAS, SAS EG, or SAS EM.

- Proficiency in credit risk concepts such as scorecards, PD, LGD, EAD, and capital modeling.

- Solid understanding of statistical modeling techniques logistic regression, decision trees, clustering, etc.

- Familiarity with regulatory requirements like Basel II/III, IFRS 9, and local regulatory frameworks.

- Strong problem-solving, analytical thinking, and data interpretation skills.

- Good communication skills and ability to translate complex models into business language.

Educational Qualification

- Masters or Bachelor's degree in Statistics, Economics, Mathematics, Quantitative Finance, or a related field