Sr. Data Scientist
Royal Bank of Canada
Senior Data Scientist
The Senior Data Scientist is responsible for delivering AI-driven intelligence, advanced analytics, and decision-support capabilities that improve advisor productivity, client engagement, operational efficiency, and regional business growth across Wealth Management. This role partners closely with regional business leadership, advisors, Data & AI teams, and Technology partners to identify high-value opportunities and rapidly deliver practical AI and analytical solutions aligned to regional priorities.
What will you do?
- Lead development of AI and analytical capabilities aligned to regional Wealth Management priorities including advisor productivity enhancement, client engagement intelligence, household insights, pipeline analytics, and attrition indicators
- Partner directly with regional business leadership and advisor teams to identify high-impact AI opportunities, prioritize use cases, and translate business challenges into analytical solutions
- Design and embed decision intelligence capabilities directly into advisor and operational workflows, including advisor copilots, meeting preparation intelligence, and opportunity scoring
- Develop and operationalize advanced analytics models including predictive models, recommendation systems, segmentation models, and NLP/GenAI-powered solutions end-to-end
- Support regional AI incubation through rapid prototyping, hypothesis testing, and iterative learning with controlled experimentation and modular solution design
- Present analytical findings and AI recommendations to leadership audiences and drive adoption of AI-enabled workflows
- Collaborate with Data Engineering and AI Engineering teams on deployment, operationalization, and continuous monitoring of analytical solutions
- Ensure all solutions align with Model Risk Management standards, data governance, privacy policies, responsible AI principles, and enterprise architecture requirements
What do you need to succeed?
Must-have
- 5+ years of experience as a Data Scientist or Analytics professional delivering machine learning and AI solutions in business environments
- Strong proficiency in Python/SQL, predictive modeling, statistical analysis, and cloud-based analytics environments
- Demonstrated ability to translate complex business problems into analytical and AI requirements with measurable success metrics
- Deep understanding of Wealth Management business models, advisor workflows, and client engagement strategies
- Strong executive communication skills with ability to simplify complex concepts and influence across business and technology teams
Nice-to-have
- Experience with Generative AI, NLP, MLOps concepts, and model lifecycle management
- Background in financial services and familiarity with financial products, portfolio concepts, and household analytics
What's in it for you?
We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.
- A comprehensive Total Rewards Program include competitive compensation and flexible benefits, such as 401(k) program with company-matching contributions, health, dental, vision, life, disability insurance, and paid-time off.
- 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.
- Opportunities to do challenging work.
- Opportunities to build close relationships with clients.
Job Skills
AI Adoption, AI Adoption, AI Agents, Algorithms, Artificial Intelligence (AI), Artificial Intelligence Techniques, Big Data Management, Business Acumen, Business Decisions, Business Outcomes, Cloud Computing, Collaboration, Commercial Acumen, Critical Thinking, Data Mining, Data Science, Data Science for Banking, Data Storytelling, Data Visualization, Data Wrangling, Decision Making, Deep Learning, Generative AI, Generative AI Agents, Knowledge Graph {+ 13 more}
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