Data Scientist III (Financial Crimes Network Analytics)
About The Position
Join the Advanced Analytics & Insights team within Financial Crimes Risk Management (FCRM) Canada to advance an innovative Financial Crimes Network Threat Detection & Prioritization capability. This high-impact initiative focuses on uncovering hidden high-risk customer connections that conventional detection methods often miss, enabling effective risk identification, prioritization, and strategic insights. The Data Scientist III will lead the enhancement & operationalization of this detection capability, primarily including developing analytical detection methods, generating risk insights, building visualization and decision-support tools for business users.
Requirements
- SQL, Python for data analytics; statistics
- Bachelor's degree in STEM (e.g., Science, Technology, Engineering, Mathematics, Statistics, Data Science, Economics).
- 1 year or above, intern / co-op experience in analytical fields is counted.
Nice To Haves
- ML/AI modelling experience
- Large Language Modelling experience
- AI agentic experience
- Anti-financial crime (money laundering, terrorist financing), regulatory and governance knowledge and working experience are beneficial but not required; training and guidance will be provided.
Responsibilities
- Translate financial crime typologies into detection strategies, generate hypothesis, design analytical approaches, develop querying logic, and validate findings through data analysis.
- Perform periodic Exploratory Data Analysis to identify emerging risk patterns, customer characteristics, and risk operation insights.
- Synthesize and present data-driven findings and recommendations to technical and non-technical audiences.
- Design and develop interactive visualization and decision-support tools that allow business users to explore identified high-risk networks, understand risk drivers, and interpret analytical outputs.
- Automate recurring operational workflows to improve scalability and efficiency.
- Develop, calibrate, and test supervised-learning model(s) for network ranking.
- Monitor model performance, evaluate existing modelling methodologies and practices, and develop new detection methodologies and analytical approaches.
- Translate business problems into structured analytical problems and develop practical solutions.
- Conduct ad-hoc analysis including such as root-cause analysis and impact analysis to meet business objectives.
- Perform independent analytical review and effective challenge of existing methodologies and analytical solutions; assess assumptions, data, results, and business implications and provide constructive recommendations for enhancement.
- Contribute to documentation, governance, controls, and ongoing monitoring required.
- Collaborate with internal team members, business users, and data engineers, technology teams, and other partners to deliver solutions.
Benefits
- health and well-being benefits
- savings and retirement programs
- paid time off
- banking benefits and discounts
- career development
- reward and recognition programs
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
