Lead AML transaction monitoring analytics at RBC in Toronto, using Python, Scala, and Spark to identify elevated financial and reputational risk.

As Lead Data Scientist, Global AML Transaction Monitoring, you will develop and maintain machine learning and rule-based solutions. You will analyze large datasets, create detection models, and improve intelligence for the Global AML program. The role also requires regulatory awareness and model risk discipline.

Key Responsibilities:
Develop, tune, and maintain AML transaction monitoring solutions
Analyze RBC client data for elevated risk
Create validation-ready model documentation and monitoring methodology
Measure model performance and recommend improvements
Identify current technologies for AML analytics

Requirements:
Five or more years conducting in-depth data analytics
University or Master degree in an analytical field
Expertise with Python and Scala or Spark
Proficiency with SQL, Hive databases, and GitHub
Understanding of AML and financial crime fundamentals

Apply data science, model monitoring, and transaction analytics expertise to strengthen RBC's Global AML program in Toronto.
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📌 Lead Aml Transaction Monitoring Scientist Toronto
🏢 RBC
📍 Toronto