Senior Consultant, Quantitative Risk Modelling
About The Position
As a Senior Consultant, Quantitative Risk Modeling in CIBC’s Client Credit Risk Analytics group, you’ll play a pivotal role in developing statistical and machine learning models and AI solutions that drive credit risk strategies for retail lending products. You’ll lead end-to-end optimization and strategy projects, collaborating with risk partners to optimize the risk/revenue tradeoff and enhance the client experience. Your expertise in modeling, data analysis, and governance will support the creation of robust models that predict key client performance metrics such as losses, delinquencies, balances, and revenues. You’ll communicate complex model results to both specialist and non-specialist audiences, maintain rigorous model governance standards, and ensure all work aligns with CIBC’s compliance policies. This role offers the opportunity to make a direct impact on CIBC’s risk management and business performance through innovative modeling and strategic insight.
Requirements
- Advanced analytics and AI experience.
- Master’s degree or PhD in a quantitative field such as analytics, statistics, mathematics, computer science, or a related discipline.
- Over 3 years of progressive experience in data analytics and machine learning, with a strong background in retail credit risk management, ideally within the banking industry.
- Expertise in agentic AI and machine learning.
- Hands-on experience developing, deploying, and monitoring agentic AI systems.
- Experience building and managing complex machine learning models for real-world applications, preferably in financial services.
- Technical mastery in Python and Databricks.
- Highly skilled in Python and extensive experience with Databricks, including managing end-to-end process and model flows.
- Comfortable with large-scale data processing, model orchestration, and applying MLOps best practices.
- Ownership mindset: results-driven, takes initiative, and demonstrates a strong sense of ownership.
- Motivated to achieve goals and deliver impactful outcomes.
- Values trust, teamwork, and accountability.
Responsibilities
- Lead the planning, development, verification, and testing of statistical and machine learning models for credit risk strategies, ensuring models meet statistical standards and business objectives.
- Architect, implement, and optimize end-to-end model development workflows in Databricks, ensuring seamless integration, reproducibility, and scalability of AI/ML models.
- Create complex strategies for production and implementation using tools such as FICO Decision Optimizer, Python, Databricks, and SAS.
- Present model results to both technical and non-technical audiences, translating technical findings into actionable business insights.
- Write model validation documentation, maintain replicable codes, and monitor model performance in alignment with model governance standards.
- Work closely with Risk Analytics, Credit Decisioning, Model Validation, and other teams to support strategy development and vetting processes.
Benefits
- Competitive salary
- Incentive pay
- Banking benefits
- Benefits program
- Defined benefit pension plan
- Employee share purchase plan
- Vacation offering
- Wellbeing support
- MomentMakers, our social, points-based recognition program
- Purpose Day; a paid day off dedicated for you to use to invest in your growth and development
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What This Job Offers
Job Type
Full-time
Career Level
Senior
