Job ID: 10224

Employment Type: New Role

Work Environment: We offer a hybrid work environment that offers flexibility to our employees in balancing in-office (2 days per week OR 15 hours per week in a Wawanesa office) and remote work. You may work from any of the following locations: Winnipeg, MB; Wawanesa, MB; Vancouver, BC; Calgary, AB; Edmonton, AB; Lethbridge, AB; Toronto (North York), ON; Kitchener, ON; Ottawa, ON; Montreal, QC; Quebec City, QC, Moncton, NB; Dartmouth; NS.

Working Business Language: English. This role is considered a head-office role and will be required to communicate with internal stakeholders across Canada where the primary business language utilized is English.

Salary: At Wawanesa, salary is only one component of a holistic, comprehensive and competitive offering that we provide to our employees. In addition to salary, full-time and part-time permanent employees are eligible for an annual bonus plan, leave of absence top-up programs and provided with generous vacation time, personal days, premium free benefits and pension plan.

The salary offered for this role is determined with consideration to various factors, including but not limited to: your work location, local labour market conditions, external market salary data, internal pay equity and the knowledge, skills, experience and anticipated proficiency in the role. The salary offered is estimated to be within the following range: $120,000 - $145,000. Candidates with salary expectations outside of the range are still encouraged to apply.

Job Overview

Reporting into the Enterprise Risk Management function, the Senior Model Risk & Validation Consultant plays a key role in independent review, validation, and challenge of models across the enterprise, including traditional statistical models, actuarial models, machine learning and AI systems.

This role supports the organization's compliance with OSFI Guideline E 23 and evolving regulatory expectations for AI governance, fairness, transparency, and explainability, while promoting strong model risk governance and risk aware decision making across the enterprise.

The successful candidate will bring strong data science and quantitative modeling expertise, combined with experience in model validation, independent review, or second line oversight, and will work with a high degree of autonomy to challenge model assumptions, methodologies, and controls.

Job Responsibilities

Independent Model Validation & Challenge

• Conduct independent validation and effective challenge of enterprise wide models across the full model lifecycle, in line with OSFI Guideline E 23.
• Review model conceptual soundness, data inputs, assumptions, methodology, performance, stability, limitations, and intended use.
• Assess model risk severity and the adequacy of controls, overlays, monitoring, and governance arrangements.
• Provide independent validation and risk challenge of AI and ML models, including data quality, bias, explainability and performance monitoring
• Evaluate model reproducibility, explainability, documentation quality, and transparency.

Model Risk Governance

• Contribute to the ongoing enhancement of the Model Risk Management Framework, including model inventory management, risk classification, validation standards and documentation requirements.
• Support Model Risk Adjudication Committee (MRAC) activities by:
  
  • Managing and updating enterprise model inventory.
  • Preparing independent validation summaries and risk assessments.
  • Tracking findings, remediation actions, and residual risk acceptance decisions.
  • Provide input into updates to model risk policies, procedures, and guidance, aligned with OSFI and AMF expectations.
  • Promote strong model development and monitoring practices across the organization through guidance, challenge, and education.
• Perform other duties as assigned.

Qualifications

• Bachelor's degree in data science, actuarial science, computer sciences, mathematics, statistics or other related discipline.
• More than six years of model development or validation experience an asset.
• Strong programming skills with Python and SQL.
• Experience validating or reviewing statistical, predictive, machine learning models and AI systems.
• Ability to clearly explain complex technical concepts to non technical stakeholders.

#LI-AF1 #LI-Hybrid