We're looking for our next Sr. Manager, Advanced Credit Risk Modelling. Could It Be You?This role will be responsible for building and guiding the day-to-day activities of our ECL frameworks using modern ML tools. You will ensure the execution of the risk modelling roadmap for IFRS 9 to a scalable modern tech stack. This role is ideal for an innovative ML/Data Science leader who has a deep understanding of credit risk regulations to satisfy Model Risk Management (MRM) standards and regulatory expectations.
Need more details? Keep reading...In this role, responsibilities include but are not limited to:
- Act as the principal hands-on developer to conceptualize, design, and build next-generation ECL, PD, LGD, EAD, and SICR models for secured and unsecured portfolios using modern ML algorithms (e.g., XGBoost, LightGBM).
- Take direct technical ownership of transitioning legacy modeling frameworks into a fully automated, scalable, and modern tech stack.
- Drive the validation process for novel ML risk models by independently implementing explainable AI (XAI) frameworks (e.g., SHAP, LIME) to satisfy rigorous Model Risk Management (MRM) and regulatory transparency requirements.
- Collaborate with MLOps and IT to establish CI/CD pipelines, automated model monitoring, drift detection, and reproducible model training frameworks.
- Contribute to building, mentoring, and growing a multidisciplinary team of quantitative analysts, ML engineers, and data scientists.
- Independently own and execute the technical delivery roadmaps for strategic credit risk and ML modernization initiatives.
- Serve as the primary technical expert, partnering closely with Credit Risk, Finance, and Regulatory teams to ensure seamless integration into IFRS 9 provisioning, capital planning, and risk appetite frameworks.
- Represent the team in working groups and cross-functional modernization initiatives.
So are YOU our next Sr. Manager, Advanced Credit Risk Modelling? You are if you have...- Master's degree or PhD in Computer Science, Artificial Intelligence, Statistics, Mathematics, Quantitative Finance, or a related field.
- A minimum of 7 years of experience in Machine Learning, Artificial Intelligence, or Advanced Analytics.
- A minimum of 7 years of experience in credit risk modelling within banking or finance.
- Deep, hands-on expertise in IFRS 9, and IRB frameworks (PD, LGD, EAD, SICR calibration) across secured and unsecured lending.
- Strong knowledge of modern ML algorithms (XGBoost, Random Forests, LightGBM) applied to credit risk.
- Excellent programming skills (Python, SQL, PySpark) and proficiency with development tools (Git, GitLab, VS Code).
- Experience with cloud platforms (AWS, Azure, GCP), data science cloud-based tools (e.g., Databricks), MLOps practices, and production deployment.
- Proven ability to successfully defend novel ML models to internal validation groups (MRM) and external regulators.
- Proficiency in Agile and SAFe methodologies and related tools (Jira, Confluence).
- Team management or leadership experience.
- Excellent communication and stakeholder management skills, with the ability to translate complex machine learning concepts into actionable business insights.
Compensation Information:- Base salary range: $140,000 - $180,000
- The final compensation package will be commensurate with the successful candidate's experience, skills, and geographic location (Canada). It includes a comprehensive benefits plan and a competitive incentive (bonus) program for Full-Time Permanent roles.
Sounds like you? Click below to apply!#LI-RJ1
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