Job DescriptionWHAT 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 new 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 GitHub
- 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.
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Job SkillsActuarial 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 DetailsAddress: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
Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above
