Data Scientist (La Prairie)

Overview

A Senior Data Scientist in the Risk Management Models team at National Bank is responsible for validating credit risk models to ensure robustness, reliability, and regulatory compliance. The role helps strengthen the bank’s regulatory credibility and supports rigorous governance of models used for regulatory capital, ICAAP, IFRS 9 and stress testing.

Responsibilities

• Assess the conceptual soundness of credit risk models, including mathematical formulation, statistical rigor, assumptions, limitations and alignment with regulatory requirements and internal standards.
• Analyze the quality, relevance and integrity of the data used in the models, including key assumptions, exclusions, outliers and documentation quality.
• Test the performance and accuracy of models using robustness and stability analyses, sensitivity tests, benchmarks and impact analyses.
• Identify model uncertainties and limitations, assess the overall level of model risk and ensure that issues are understood, documented and adequately escalated in the governance framework.
• Draft clear, rigorous and well‑structured validation reports highlighting findings, conclusions and impacts on the use of models and risk management.
• Support the team during regulatory reviews, internal and external audits by providing solid technical expertise and high‑quality documentation.
• Maintain collaborative relationships and act as an expert with key stakeholders (modeling teams, model owners, model risk management and senior management) by providing independent judgment, expert advice and sound recommendations.
• Recommend and implement improvements to the validation framework and practices to meet internal needs and align with regulatory requirements and industry practices.

Qualifications

• Master’s or bachelor’s degree in statistics, actuarial science, finance, economics, mathematics or a related quantitative field.
• Approximately five years or more of relevant experience in a financial institution in credit risk modeling and/or model validation.
• Advanced expertise in statistical methods and credit risk modeling, including key parameters such as probability of default, loss given default and exposure at default.
• Solid knowledge of ICAAP and IFRS 9 frameworks and their governance and modeling implications.
• Mastery of the Basel II and III regulatory framework and its application to credit risk models and capital requirements.
• Excellent knowledge of analytical and programming tools such as SAS Viya, SAS Enterprise Guide, SQL, Python, MATLAB, R or equivalent.

Benefits

• Health and wellness program, including many options.
• Flexible group insurance.
• Generous pension plan.
• Employee Share Ownership Plan.
• Employee and family assistance program.
• Preferential banking services.
• Involvement in community initiatives.
• Telemedicine service.
• Virtual sleep clinic.

We welcome all candidates.