Senior Data Scientist – IFRS 9 & Credit Risk Analytics

National Bank of Canada; Richmond Hill; On-site; CAD 110,000 - 170,000; Full time

Benefits offered by this job

Health and wellness program

Generous pension plan

Employee Share Ownership Plan

Employee and family assistance program

Preferential banking services

Job summary

National Bank of Canada seeks a Senior Data Scientist in Credit Risk Analytics to lead IFRS 9 and stress testing model development, validation, and reporting. You will work on ECL, RWA, and Economic Capital, collaborating with Validation and Audit to ensure robust governance and timely delivery.

Ideal candidates have 2–3+ years in quantitative credit risk modeling, fluency with SAS/Python/SQL, and knowledge of IFRS 9 regulations, data management, and advanced analytics.

Qualifications

• Masters or PhDs in a relevant field; CFA/FRM would be an asset.
• Minimum 2-3 years of quantitative model development or validation experience in credit risk.
• Hands-on experience with SAS, Python, SQL, and Excel; knowledge of IFRS 9 regulatory requirements.

Responsibilities

• Develop and recalibrate IFRS 9 and stress testing models for wholesale and retail portfolios; document methods and data selection.
• Validate inputs/outputs for quality control and governance; monitor model performance.
• Collaborate with Model Validation and Audit to document IFRS 9 changes and ECL calculations; analyze drivers of ECL movements.
• Provide ad-hoc support to IFRS 9 stakeholders and senior management with precise analyses.
• Develop IFRS 9 PCL budget and monitor the bank's risk limits.

Skills

AI/ML knowledge

Analytical thinking

Problem solving

Teamwork

Detail-oriented

Data-driven decision-making

Data Structures

Education

Masters or PhDs in Financial Engineering, Finance, Economics, Statistics, Mathematics, Computer Science or Data Science

Tools

SAS

Python

SQL

MS Excel (VBA)

Job description

National Bank of Canada seeks a Senior Data Scientist in Credit Risk Analytics to lead IFRS 9 and stress testing model development, validation, and reporting. You will work on ECL, RWA, and Economic Capital, collaborating with Validation and Audit to ensure robust governance and timely delivery.

Ideal candidates have 2–3+ years in quantitative credit risk modeling, fluency with SAS/Python/SQL, and knowledge of IFRS 9 regulations, data management, and advanced analytics.