Credit Risk Modeling Expert

Technologies we use

Your responsibilities

• Model Development:
• Develop expected loss forecasting models (PD/LGD/EAD) with best practice and document model methodology, selection evidence, model performance testing for validation and regulatory review.
• Review and revise segmentation and modeling approach based on changes in business unit, portfolio or economic intuition.
• Analyze model metrics (e.g., accuracy, stability), identify issues, and recommend improvements.
• Coding: Use various programming languages (Python, SAS, SQL, R) in development and data analysis. Write and execute code in both local environment and cloud platforms (Azure or others).
• Model Review: Provide effective challenges to existing and new models to identify the potential weak points and enhance model performance.
• CCAR/CECL Submission: Provide support for stress testing (CCAR) submission and CECL process; document associated portfolios analysis, respective overlays for emerging risks and reasonableness analysis; respond questions from senior management and regulators in a timely manner.
• Transformation: Leverage automation tools and Al to increase efficiency, reduce operational risk, and enhance usability and interpretability of results.

Our requirements

• Master's Degree or PhD in a quantitative field such as computer science, data science, mathematics, or statistics.
• 5 or more years of experience in credit risk modeling and industry-standard approaches (e.g. PD, LGD, EAD).
• Deep understanding of banking, financial metrics, and credit risk management.
• Knowledge of banking regulation and requirements for stress testing and credit reserves.
• Programming experience in Python (preferred) or similar statistical software (e.g. SAS, R)
• Strong analytical and problem-solving skills, coupled with thoroughness and attention to detail
• Effective interpersonal, verbal, and written communication skills.

Optional

• Experience with cloud-based tools and infrastructure (Azure or others).
• Experience working with large datasets and building or validating advanced statistical models (including regression and economic factor models)
• Exposure to machine learning concepts and their application in financial services.
• Understanding of version control systems like Git.

What we offer

• Clearly defined salary ranges aligned with industry benchmarks and internal equity standards.
• Performance-based incentives for eligible employees (as defined by relevant plan rules), awarded through transparent, objective criteria that recognize both individual and company performance.
• Inclusive equitable benefits that are accessible to all employees and focused around our 3 main pillars of financial wellbeing, health & wellness).
• Continuous development opportunities including training, education support, and career progression pathways based on inclusive and transparent criteria.
• Employee recognition programs that celebrate achievements and milestones for all.

Benefits

About the Role

• In this role, you will develop and implement expected loss forecasting models for Commercial Real Estate (CRE), Commercial Industrial (C&I), or Small Business portfolios, ensuring compliance with CECL, CCAR, and other regulatory requirements.
• The ideal candidate brings strong predictive modeling expertise, solid knowledge of commercial portfolios, statistical methods, and U.S. banking regulations, along with excellent communication skills and strong attention to detail.