Description
A career as a senior credit risk analyst in the Credit Risk Analytics team at National Bank means contributing as a specialist in IFRS‑9 reporting, modelling and analytics. This role allows you to have a positive impact on the organization thanks to your experience in credit risk modelling, your ability to navigate regulatory requirements, and your strengths in complex data analysis.
Your role
- Operate and maintain IFRS‑9 expected credit loss (ECL) reporting processes to ensure timely and accurate results
- Validate process inputs and outputs to uphold quality control and governance standards
- Conduct analyses of IFRS‑9 results and identify key drivers behind ECL movements
- Prepare ECL materials and insights for internal partners, external auditors and regulatory stakeholders
- Assess IFRS‑9 impacts related to recalibration, scenario changes, model updates, data migration and process improvements
- Support IFRS‑9 and stress testing model development, backtesting, and performance monitoring
Your team
The Credit Risk Analytics sector brings together 24 specialists who work collaboratively and proactively to stay at the forefront of risk modelling, reporting and regulatory expectations.
Within this sector, you are part of a large team of colleagues and you report to the Senior Director. Our team stands out for its expertise in IFRS‑9 modelling, stress testing and implementation, as well as its rigorous risk reporting processes. At times, certain deliverables fall within month‑end or quarter‑end reporting cycles, which can require operating under tight deadlines. We aim to offer you maximum flexibility to support your well‑being through a hybrid work environment and adaptable scheduling.
National Bank values continuous development and internal mobility. Our tailored training programs, based on learning through action, help you deepen your skills and explore new expertise. Tools such as the Data Academy, language training, the Harvard Learning Center, coaching and mentoring are accessible to you at all times.
Prerequisites
- Master’s degree in a relevant field such as Financial Engineering, Finance, Economics, Statistics, Mathematics, Computer Science or Data Science or any related degree in the field
- 2-3 years of relevant experience in risk management or credit risk analytics
- Hands‑on experience manipulating, interpreting and reconciling large‑scale datasets
- Knowledge of IFRS‑9 and related regulatory expectations
- Practical experience using SAS, Python, SQL and advanced Excel
- Experience supporting model development, backtesting or performance monitoring