Develop IFRS 9 and stress testing models at National Bank, using Python, SAS, SQL, and strong credit risk analytics expertise. Support wholesale and retail portfolios.

As a Senior Data Scientist in Credit Risk Analytics, you will develop, recalibrate, and monitor quantitative models. You will analyze IFRS 9 results, assess expected credit loss impacts, and support related risk functions including RWA and Economic Capital. Your work will inform credit risk management and senior management analysis.

Key Responsibilities:

- Develop and recalibrate IFRS 9 and stress testing models
- Document data selection, modeling techniques, and implementation
- Conduct backtesting and monitor model performance
- Assess expected credit loss impacts from model and process changes
- Analyze IFRS 9 results and identify ECL movement drivers

Requirements:

- Master’s or PhD in a relevant quantitative field
- Two to three years in credit risk model development or validation
- Knowledge of IFRS 9 and regulatory requirements
- Experience with SAS, Python, MS Excel VBA, or SQL
- Robust analytical and communication skills

Apply credit risk modeling, IFRS 9 expertise, and analytical skills to strengthen National Bank’s risk management capabilities.

📌 Senior IFRS 9 Credit Risk Scientist (Richmond Hill)
🏢 National Bank of Canada
📍 Richmond Hill