Senior Data Scientist, Credit Risk in Richmond Hill

Senior Data Scientist, Credit Risk in Richmond Hill

Richmond Hill Full-Time 115731 - 141449 $ / year (est.) Hybrid
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At a Glance

  • Tasks: Develop and enhance credit risk models using AI and advanced data analysis.
  • Company: Join National Bank's innovative Credit Risk Analytics team.
  • Benefits: Flexible work environment, health programs, and employee share ownership.
  • Other info: Collaborative culture with continuous learning and growth opportunities.
  • Why this job: Make a real impact in risk management while advancing your career.
  • Qualifications: Master's degree and 3-5 years in risk analytics or related fields.

The predicted salary is between 115731 - 141449 $ per year.

A career as a Senior Data Scientist in the Credit Risk Analytics team at National Bank means acting as a hands-on subject matter expert in credit risk modelling and economic capital (EC) analytics. This role allows you to have a positive impact on the organization through your expertise in quantitative modelling, risk measurement, economic capital estimation, AI and advanced data analysis.

Your role:

  • Develop and enhance Credit Economic Capital (EC) and ICAAP processes to support new product launch, new portfolio integration, data migration, and internal and external reporting requirements.
  • Develop and enhance EC, ICAAP, and concentration risk models.
  • Modernize EC, ICAAP, and other risk reporting processes with effective use of AI tools, improving efficiency, automation, and analytical capabilities.
  • Manage and execute EC and ICAAP production and reporting processes to support monthly and quarterly risk measurement activities.
  • Perform in-depth analysis of capital results, identify key drivers of capital movements, and prepare clear and insightful materials for senior management, internal stakeholders, and regulators.
  • Support model development, implementation, and back-testing across other credit risk areas, including IFRS 9 and stress testing.
  • Collaborate with Finance, IT, Business, AIRB Model Development, Model Validation, and Internal Audit to support model development initiatives and analytical projects.

Your team:

The Risk Management team brings together highly specialized professionals who work collaboratively to strengthen the Bank’s risk management practices and analytical capabilities. Within the Credit Risk Analytics group, you will be part of a specialized EC team and report to the Senior Director, Credit Risk Analytics. Based in Richmond Hill, Ontario, the group is responsible for model development, model implementation, and risk reporting across Capital, IFRS‑9 and stress testing.

Requirements:

  • Hold a master's degree in a relevant field such as data science, financial engineering, statistics, mathematics, economics, computer science, or a related discipline.
  • Have 3 to 5 years of experience in risk management, credit risk analytics, risk modelling, risk reporting, or a related quantitative discipline within a financial institution.
  • Demonstrate strong programming capabilities using tools such as Python, SQL, SAS, or other analytical programming languages.
  • Demonstrate ability to effectively and efficiently use AI tools to support quantitative modelling, risk analysis and reporting.
  • Possess advanced quantitative and statistical modelling expertise, with experience developing, validating, or supporting risk models.
  • Have experience working with economic capital models, stress testing, credit risk measurement frameworks, or related risk analytics methodologies.
  • Knowledge of Moody’s RiskFrontier platform or similar credit portfolio risk management solutions is considered an asset.
  • Ability to learn quickly in a dynamic and evolving environment.
  • Adaptability and flexibility when responding to changing priorities and urgent business needs.
  • Strong analytical thinking and problem-solving skills.
  • Ability to manage multiple priorities while maintaining a high level of accuracy.
  • Collaborative mindset and willingness to contribute across teams.
  • Curiosity and openness to leveraging new technologies, including artificial intelligence tools, to improve efficiency.

In addition to competitive compensation, upon hiring you’ll be eligible for a wide range of flexible benefits to help promote your wellbeing and that of your family such as:

  • Health and wellness program, including many options
  • Employee Share Ownership Plan
  • Employee and family assistance program
  • Preferential banking services
  • Involvement in community initiatives
  • Virtual sleep clinic

We value employees’ ideas. Whether through our surveys or programs, regular feedback and ongoing communication are encouraged. We’re a bank on a human scale that stands out for its courage, entrepreneurial culture, and passion for people. Our mission is to have a positive impact on people’s lives. Our core values of partnership, agility, and empowerment inspire us, and inclusion is central to our commitments.

We strive to provide accessibility measures throughout the recruitment process within the limits of our available resources. If you require accommodations, feel free to let us know during our initial conversations. We welcome all candidates!

Senior Data Scientist, Credit Risk in Richmond Hill employer: Banque Nationale du Canada

At National Bank of Canada, we pride ourselves on fostering a dynamic work culture that prioritizes employee growth and collaboration. As a Senior Advisor in Consumer Protection Compliance, you will benefit from a hybrid work arrangement, allowing for flexibility while engaging with senior leadership and shaping our compliance framework. Our commitment to regulatory excellence and risk management ensures that you will be part of a team that values your expertise and encourages meaningful contributions.

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Contact Details:

Banque Nationale du Canada Recruitment Team

We think you need these skills to ace Senior Data Scientist, Credit Risk in Richmond Hill

Credit Risk Modelling
Economic Capital Analytics
AI Tools Utilization
Quantitative Modelling
Risk Measurement
Data Migration
Model Development