Director, Data Science

RBC

Director leading the Data Science team at RBC focused on AI and analytics innovations. Overseeing model development and ensuring data governance across distribution networks in Canada.

Posted 6/14/2026full-timeToronto • 🇨🇦 CanadaLeadWebsite

ATS Keywords

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Hard Skills

data scienceartificial intelligenceadvanced analyticsmachine learningdeep learningnatural language processingdata governancemodel risk managementmodel developmentmodel deployment

Soft Skills

leadershipcollaborationinnovationbusiness acumenstrategic recommendationscommunicationteam managementproblem-solvingcontinuous learningcross-functional collaboration

Certifications & Qualifications

Bachelor's degreeMaster's degreePhD

Industry Keywords

data qualityregulatory compliancedigital transformationdata modernizationfinancial regulatory requirementsmodel governance standardsAI capabilitiesclient experiencetechnology investmentsdata accessibility

About the role

Key responsibilities & impact

Join RBC as a Director to lead the Data Science team for the AI, Conversational Banking & Platforms team
Drive transformational change across the distribution network through advanced analytics and innovative AI modeling solutions
Lead a high-performing team transforming rich data into AI capabilities
Implement solutions that enhance decision-making and client experience across RBC's distribution network
Oversee the full lifecycle of AI and machine learning model development
Establish comprehensive frameworks to ensure data quality, accessibility, and governance
Collaborate with peer leadership and business units to identify high-value data science opportunities
Provide strategic recommendations on emerging technologies, vendor partnerships, and technology investments
Partner with the AI Product team to translate business requirements into data science solutions
Work across technology and data engineering teams to ensure scalable, reliable, and maintainable model deployment in production environments
Cultivate an organizational culture that prioritizes innovation, cross-functional collaboration, and continuous learning.

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering, or related quantitative discipline
10+ years of progressive experience in data science, artificial intelligence, and/or advanced analytics
Expertise in machine learning, deep learning, natural language processing, and AI techniques
Demonstrated expertise leading high-performing technical teams while maintaining hands-on proficiency in analytics and modeling
Deep understanding of data governance principles, model risk management frameworks, and regulatory compliance requirements
Strong business acumen and ability to translate technical concepts into business value and strategic impact
Advanced degree (Master's or PhD) in Computer Science, Statistics, Mathematics, or related field (Nice to Have)
Track record of leading enterprise-wide digital transformation or data modernization initiatives (Nice to Have)
Proven experience successfully developing, validating, and deploying machine learning models at scale in production environments (Nice to Have)
Demonstrated knowledge of financial regulatory requirements and model governance standards (Nice to Have).

Benefits

Comp & perks

A comprehensive Total Rewards Program including bonuses and flexible benefits
Competitive compensation
Commissions and stock where applicable
Leaders who support your development through coaching and managing opportunities
Ability to make a difference and lasting impact
Work in a dynamic, collaborative, progressive, and high-performing team
A world-class training program in financial services
Opportunities to take on progressively greater accountabilities.