- Develop credit risk models using SAS, SQL, and statistical modeling techniques to predict defaults, losses, and other credit-related metrics.
- Collaborate with cross-functional teams to design and implement effective credit risk strategies that meet business objectives.
- Conduct stress testing and scenario analysis to identify potential risks and opportunities for growth.
- Provide data insights and recommendations to stakeholders on loss forecasting, scorecards, and portfolio performance.
Desired Candidate Profile
- 2+ years of experience in Credit Risk Modelling, Analytics, or a related field.
- Strong expertise in Basel II, Basel III, CECL, and CCAR within the IFRS9 framework.
- Proficiency in Python, R, or SAS, with a solid understanding of machine learning algorithms as an added advantage.