Data Scientist, Transaction Monitoring As Data Scientist, Transaction Monitoring, you will develop and maintain an efficient and effective AML/ATF Transaction Monitoring program that considers regulatory expectations, industry trends and innovation opportunities. Utilizing sophisticated tools and techniques, you will also 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, maintain, and improve Transaction Monitoring solutions with data science techniques as well as related Model White Papers for all Transaction Monitoring solutions
Through quantitative and qualitative analysis establish thresholds and parameters used in monitoring solutions
Present newly developed monitoring solutions with explicit visualizations to the Senior Manager, Global AML Transaction Monitoring Data Science
Identify opportunities in applying new technologies to AML Transaction Monitoring
Expand Transaction Monitoring model coverage in Capital Markets, Wealth Management, and Investor Services
Manage independent reviews (auditors, regulators, Model Validation etc) of monitoring solutions
Act as SME for data requirements used in Transaction Monitoring solutions




Provide recommendations to the Senior Manager, Global AML Transaction Monitoring Data Science on any findings of model performance
Collaborate with the Senior Manager 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
Transaction monitoring innovation lead for new analytics/quantitative transaction monitoring methods and technologies
What do you need to succeed? Must Have Strong data, analytical, quantitative method and problem-solving skills
Expertise in analyzing and manipulating large datasets with Python
Proficiency and familiarity with different SQL or HIVE databases and Git Hub
Strong capability in exploratory data analysis and feature development
Experience in using data visualizations to elaborate model performance with Python
Understands project's needs and ability to translate these into detection models
Experience with supervised and unsupervised learning, and network analysis is a plus
Proven excellent written and oral communication skills to convey complex concepts to a non-technical audience
Knowledge of Banking products is a bonus (Cash Management, Equity, Fixed Income, Commodities, Derivatives, Wire, Electronic ACH, E-

📌 Data scientist, global aml transaction monitoring (Toronto)
🏢 RBC
📍 Toronto