Product Manager defining and scaling responsible data and AI products at iA Financial Group. Driving roadmaps, experimentation, governance, and cross - functional delivery.
About the role
- Lead Data Scientist developing AML transaction-monitoring models for RBC, a major Canadian bank. Applying machine learning, rules, and analytics to identify financial crime risk.
Responsibilities
- Develop, tune, and maintain AML Transaction Monitoring machine learning and rule-based solutions
- Develop new AML Transaction Monitoring solutions using data science techniques
- Develop validation-ready model documentation and monitoring methodology in adherence to Enterprise Model Risk Management Standards
- Create and document model performance metrics and provide recommendations to the Director, Transaction Monitoring
- Collaborate with the Director, Transaction Monitoring to prioritize development of monitoring solutions
- Collaborate with Monitoring & Analytics teams to identify and remediate RBC risk exposure and implement or tune transaction monitoring solutions
- Collaborate with business partners and internal stakeholders to improve transaction monitoring effectiveness and efficiency
- Identify opportunities to apply new technologies to AML analytics
- Identify industry best practices and new technologies for strategic consideration by the AML Monitoring and AML Governance Committee
- Analyze data to identify RBC clients presenting elevated financial or reputational risk
- Provide relevant and valuable intelligence to the Global AML program
Requirements
- 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 SQL, Hive databases, and GitHub
- Strong capability in exploratory data analysis and feature development
- Understanding of AML and Financial Crime Fundamentals
- Ability to synthesize 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 technical and non-technical stakeholders
- Understanding of project needs and ability to translate these into detection models
Benefits
- 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 and take on progressively greater accountabilities
- Access to a variety of job opportunities across business and geographies
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