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 new 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.
Lead AML Transaction Monitoring Scientist in Toronto employer: RBC
RBC is an exceptional employer that fosters a dynamic and inclusive work culture, where innovation thrives and employees are empowered to grow. As a Senior Director in Toronto, you will lead a talented team in developing cutting-edge AI solutions that transform the banking experience for millions, while enjoying comprehensive benefits, professional development opportunities, and a commitment to community impact. Join us to be part of a collaborative environment that values diverse perspectives and champions your success.
