Description
Note: When applying for this position, please ensure you use your external-facing profile / resume to avoid screening rejection.
- Looking for SG5/SG6 candidates.
- 3+ years of experience in Credit Risk Analytics or Model Implementation.
- Strong programming experience in Base SAS and SAS Enterprise Guide.
- Positive understanding of credit risk modelling concepts, model implementation pipeline, risk scoring process, IFRS9/CECL concepts, including PD, LGD, EAD, and ECL.
- Experience with SQL, data validation, testing, impact analysis and production support.
- Knowledge of Model Risk Management / Model Governance frameworks and practices. • Working knowledge of the Linux environment.
- Exposure to Python, Google Cloud Platform (GCP), or automation tools is an added advantage.
- Exposure to AI/LLM model usage is an added advantage.
- Exposure to Banking or Non-Banking Financial Lending is an added advantage.

Responsibilities
- Implement, validate, test, and Productionalize predictive models and risk strategies across global platforms.




- Collaborate with Data Scientists, Business teams, and IT to ensure smooth transition of models from development to production.
- Implement and maintain credit risk models (Scorecard models, PD, LGD, other risk models) using SAS.
- Perform code development, testing, reconciliation, and production deployment for model enhancements and business logic changes.
- Support production execution and impact analysis and resolve implementation issues within agreed timelines.
- Collaborate with Model Development, IT, and business stakeholders to implement model enhancements and change requests.
- Prepare technical and workflow/process documentation and support internal and external audits.
- Drive automation and continuous process improvements by proactively identifying opportunities to enhance operational efficiency.
- Identify opportunities to introduce automation, GenAI tooling, and workflow simplification and develop Proof-of-Concepts

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