Senior Data Scientist: IFRS 9 & Credit Risk Modeling

National Bank of Canada; Richmond Hill; On-site; CAD 120,000 - 160,000; Full time

Benefits offered by this job

Health and wellness program

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

Job summary

National Bank of Canada is seeking a Senior Data Scientist for the Credit Risk Analytics team to drive IFRS 9 and stress testing model development, performance monitoring, and reporting. The role supports RWA, Economic Capital and related risk functions, delivering advanced models and robust risk processes for senior management.

Ideal candidates have strong credit risk modeling experience, knowledge of IFRS 9, and proficiency in SAS, Python, and SQL, with a track record of delivering insights

Qualifications

• Masters or PhDs in a relevant field such as Financial Engineering, Finance, Economics, Statistics, Mathematics, Computer Science and Data Science.
• Completion or progression in CFA and/or FRM would be an asset.
• Completion of SAS certification would be an asset.
• Minimum 2-3 years of professional experience in quantitative model development or validation for retail or wholesale credit risk.
• Hands-on experience in managing, reconciling, and interpreting large and complex enterprise level data sets.
• Knowledge with IFRS 9 and regulatory requirements.
• Hands-on experience with SAS, Python, MS Excel (VBA) or SQL.
• Knowledge of AI and Machine Learning would be an asset.
• Excellent analytical skills to identify the causes of risk changes and impact to business and strategy.

Responsibilities

• Develop and recalibrate IFRS 9 and stress testing models for the Bank’s wholesale and retail portfolios. Document the data selection, modeling techniques and implementation.
• Keep abreast of up-to-date modeling methodologies, tools and regulatory requirements.
• Conduct IFRS 9 ECL impact assessment for parameter recalibration, economic scenario change, model updates, data migration and process changes.
• Implement IFRS 9 model changes in the ECL calculation process, including updating, testing and maintaining the IFRS 9 ECL calculation engine.
• Validate the process inputs and outputs for quality control and governance.
• Review, identify and recommend process improvement opportunities for IFRS 9 ECL calculation engine.
• Collaborate with Model Validation, Model Governance, Audit by preparing supporting materials, addressing questions and concerns, and ensuring IFRS 9 model changes and ECL calculation updates are appropriately documented and understood.
• Provide in-depth analysis on IFRS 9 results and identify key drivers for ECL movements.
• Develop, manage and monitor IFRS 9 PCL budget and limit for the bank.
• Provide support for ad-hoc requests required by IFRS 9 stakeholders and senior management in a precise and efficient manner.
• Contribute to strategic risk initiatives by using analytical skills to project potential losses and make recommendations to limit risk.
• Demonstrate insight into internal client's business and develop innovative solutions that create value.

Skills

Python

SQL

SAS

Excel VBA

Machine Learning

Data Analysis

Education

Master's or PhD in a relevant field

CFA/FRM (asset)

SAS certification (asset)

Tools

SAS

Python

SQL

MS Excel (VBA)

Job description

National Bank of Canada is seeking a Senior Data Scientist for the Credit Risk Analytics team to drive IFRS 9 and stress testing model development, performance monitoring, and reporting. The role supports RWA, Economic Capital and related risk functions, delivering advanced models and robust risk processes for senior management.

Ideal candidates have strong credit risk modeling experience, knowledge of IFRS 9, and proficiency in SAS, Python, and SQL, with a track record of delivering insights