WHAT IS THE OPPORTUNITY? As a Lead Data Scientist, Global AML Transaction Monitoring, you will develop and maintain efficient and effective AML/ATF Transaction Monitoring models that considers regulatory expectations, industry trends and innovation opportunities.
You will be required to develop and tune new and existing solutions used to identify suspicious activity, analyze data to identify RBC clients who present an elevated level of risk (financial reputational) and continuously look for opportunities to provide more relevant and valuable intelligence to the Global AML program.
WHAT WILL YOU DO? Develop, tune, and maintain existing AML Transaction Monitoring machine learning, rule-based solutions

Develop new AML Transaction Monitoring solution using machine learning and/or other advanced data science techniques

Develop validation-ready model documentation and monitoring methodology for models, in adherence to Enterprise Model Risk Management Standards

Create and document model performance metrics, and provide recommendations to the Director, Transaction Monitoring on any findings of model performance

Collaborate with the Director, Transaction Monitoring to prioritize development of monitoring solutions

Collaborate with other Monitoring & Analytics teams to identify and remediate RBC risk exposure, and implement / tune transaction monitoring solutions as necessary to address risk

Collaborate with business partners and internal stakeholders to improve effectiveness and efficiency of transaction monitoring program

Identify opportunities in applying recent technologies to AML analytics

Identifying industry best practices and new technologies for strategic consideration by the AML Monitoring and AML Governance Committee

WHAT DO YOU NEED TO SUCCEED? Must have: 5+ years of experience conducting in-depth data analytics

University or Master degree in an analytical field of study (e.g. Computer Science,



Engineering, Mathematics, Statistics, or related quantitative field).
Expertise in analyzing and manipulating large datasets with Python and Scala/Spark
Proficiency and familiarity with different SQL, Hive databases and Git Hub
Experience with supervised and unsupervised learning, and NLP
Strong capability in exploratory data analysis and feature development
Understanding of AML and Financial Crime Fundamentals
Strong solution-oriented mindset, capable of synthesizing technical, operational and business context into clear understanding of how models operate
Exceptional attention to detail across documentation, testing artifacts, and quantitative analysis

Strong written and verbal communication skills; capable of explaining model risk analytics findings to both technical and non-technical stakeholders, as well as tell stories with data meaningfully

Understands project's needs and ability to translate these into detection models

Nice-to-have: Specific experience in Financial Crime or Transaction Monitoring Analytics roles

Experience working in specific business data domains (i.e. Capital Markets, Wealth Management)

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 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 do challenging work. Opportunities to take on progressively greater accountabilities. Opportunities to building close relationships with clients
Access to a variety of job opportunities across business and geographies.
Job Skills Actuarial Modeling
Big Data Management
Commercial Acumen
Data Mining
Data Science
Decision Making
Machine Learning (ML)
Natural Language Processing (NLP)
Predictive Analytics
Python (Programming Language)
Additional Job Details Address: 20 KING ST W:TORONTO
City: Toronto
Country: Canada
Work hours/week: 37.5
Employment Type: Full time
Platform: GROUP RISK MANAGEMENT
Job Type: Regular
Pay Type: Salaried
Posted Date: 2026-07-16
Application Deadline: 2026-08-16

Our Employment Opportunities 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.

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📌 Lead Data Scientist, AML Analytics (Vancouver)
🏢 RBCx
📍 Vancouver