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About the Role

RBC is a global leader in applying Artificial Intelligence (AI) in the banking sector to create value for clients. The AI validation team within RBC's Enterprise Model Risk Management is tasked with overseeing, assessing, and managing the model risk that may arise from AI capabilities. The team uses machine learning, statistical, and computational strategies to assess model risk, identifying model weaknesses early and enhancing the reliability of production models.

Responsibilities

• Design and execute validation frameworks, exploring modelling considerations such as conceptual soundness, data processing, metric reproducibility & stability, benchmarking, robustness, uncertainty quantification, fairness, privacy, explainability, and implementation controls.
• Read research papers to enhance model validation processes and contribute to the team's knowledge pool.
• Apply learned concepts to real-world problems, develop reusable software packages, and share insights.
• Collaborate with cross-functional stakeholders to establish and promote best-practices related to MLOps, tooling, and IT infrastructure.
• Work with model developers and business stakeholders to inventory AI/ML applications, determine materiality, and assess review requirements.

Requirements

• Passionate about learning and staying up-to-date with research and technology.
• Strong communication and interpersonal skills.
• Progress towards a PhD or Master’s degree in Statistics, Computer Science, Applied Mathematics, Econometrics, Engineering, Quantitative Finance, or a related quantitative field.
• Proficient programming skills in Python or a similar language.
• Comfortable with writing research experiments.
• Willing to learn how to write clean code.
• Familiarity with popular machine learning frameworks and libraries.
• A risk-oriented mindset.
• Publication or prior research experience (applied or fundamental).
• Experience with version control systems.
• Comfortable with command line tools.

Skills

• Client Counseling
• Communication
• Critical Thinking
• Financial Instruments
• Group Problem Solving
• Investment Risk Management
• Market Risk
• Quantitative Methods
• Risk Management
• Python
• Machine Learning Frameworks
• MLOps

Location

• ROYAL BANK PLAZA, 200 BAY ST:TORONTO
• Toronto
• Canada

Work Type

• Full time

Education Level

• PhD or Master’s degree in Statistics, Computer Science, Applied Mathematics, Econometrics, Engineering, Quantitative Finance, or a related quantitative field

About the Company

• RBC is a global leader in applying Artificial Intelligence (AI) in the banking sector.
• At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC.
• We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world.
• Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities.
• RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.