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Manager, IFRSModelling, Enterprise Stress Testing

Job in Toronto, Ontario, M5A, Canada
Listing for: Scotiabank
Full Time position
Listed on 2026-06-20
Job specializations:
  • Finance & Banking
    Risk Manager/Analyst, Data Scientist
Job Description & How to Apply Below
Position: Manager, IFRS9 Modelling, Enterprise Stress Testing

Is this role right for you?

In this role you, will:
  • Model Development:
    Design and develop credit risk stress testing models that forecast credit quality migration under stressed macroeconomic conditions for retail portfolio. This involves models for PD, downgrade rates, and LGD.
  • Stress Test Implementation:
    Apply these models to generate stress testing results – including ECL, PCL, and RWA – under various macroeconomic scenarios. Continuously optimize code repositories to ensure efficiency, accuracy, and production-readiness.
  • Result Analysis and Reporting:
    Conduct detailed analysis to validate the accuracy and explainability of model outputs. Develop robust data visualization tools and standards to support complex scenario analysis. Prepare and deliver stress testing reports to internal stakeholders and external regulators, including OSFI.
  • Emerging Risk Analysis:
    Perform supplementary analyses and develop methodologies to address emerging risk themes such as climate change, geopolitical instability, elevated consumer indebtedness, and housing market pressures etc.
  • Cross-Functional Collaboration:

    Collaborate with model validation, internal audit, and other model development teams (e.g., AIRB, IFRS 9, Capital Management) to ensure alignment with industry best practices and maintain model compatibility and compliance across frameworks.
  • Do you have the skills that will enable you to succeed in this role? - We'd love to work with you if you have:

  • Advanced degree in Statistics, Economics, Finance, Mathematics, Data Science, or a related quantitative discipline.
  • Proven expertise in quantitative modeling, including statistical analysis, econometrics, machine learning, and data science techniques.
  • Proficiency in Python is required; experience with Spark is considered an asset.
  • Familiarity with Linux or UNIX systems and version control tools such as Git or Bitbucket is advantageous.
  • Demonstrated experience working with large and complex datasets and optimizing code for performance and scalability.
  • Hands-on experience in credit risk modeling, particularly related to Probability of Default (PD) and/or Loss Given Default (LGD).
  • Exposure to stress testing frameworks and methodologies is desirable.
  • Strong communication skills, with the ability to convey complex analytical insights to diverse audiences.
  • Solid understanding of banking financial statements, retail credit products, and credit risk modelling.
  • Working knowledge of Risk-Weighted Assets (RWA) and Basel capital requirements is an asset.
  • Experience leading or contributing to transformational projects.
  • Track record of presenting analytical findings and business insights effectively.
  • What’s in it for you?

  • The opportunity to join a forward-thinking company surrounded by a collaborative team of innovative thinkers.
  • A rewarding career path with diverse opportunities for professional development. This position will have exposure to multiple aspects of the bank’s financial profile, such as balance sheet growth, provisions for credit losses and capital adequacy assessment.
  • Becoming a subject matter expert and storyteller for our Canadian retail portfolio, in terms of how the stress testing process works and what drives the portfolio’s credit loss
  • A competitive compensation and benefits package.
  • An organization committed to making a difference in our communities– for you and our customers.
  • We have an inclusive and collaborative working environment that encourages creativity, curiosity, and celebrates success!
  • Note that applications are not being accepted from your jurisdiction for this job currently via this jobsite. Candidate preferences are the decision of the Employer or Recruiting Agent, and are controlled by them alone.
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