Data Scientist III - Financial Crimes Network Analytics; ATH

Position: Data Scientist III - Financial Crimes Network Analytics (ATH 5556)
## Data Scientist III - Financial Crimes Network Analytics (ATH 5556)
Apply:
Office Focused:
Toronto, Ontario:
Markham, Ontario:
Full time:
Posted Today:
End Date:
October 17, 2026 (10 days left to apply):
R 1514553
*
* Work Location:

** Toronto, Ontario, Canada
*
* Hours:

** 37.5
** Line of Business:
** Analytics, Insights, & Artificial Intelligence
** Pay Details:**$96,900 - $136,800 CADTD is committed to providing fair and equitable compensation opportunities to all colleagues. Growth opportunities and skill development are defining features of the colleague experience  compensation policies and practices have been designed to allow colleagues to progress through the salary range over time as they progress in their role. The base pay actually offered may vary based upon the candidate's skills and experience, job-related knowledge, geographic location, and other specific business and organizational needs.

As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.
*
* Job Description:

*
* ** Data Scientist III ( Financial Crimes Network Analytics )*
* ** Summary
* * 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.  
** Key Accountabilities
**** Financial Crime Analytics & Detection
*** 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.  
** Technical Solutions & Operationalization
*** 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.  
** Modelling & Innovation
*** 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  
** Ad-hoc Analysis
*** 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  
** Stakeholder Management
*** Collaborate with internal team members, business users, and data engineers, technology teams, and other partners to deliver solutions.

** Qualifications & Skills**
* ** Core skills**: SQL, Python for data analytics; statistics;
* ML/AI modelling experience, Large Language Modelling experience, AI agentic experience are bonus.
* ** Domain knowledge**:
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.
* ** Education**:
Bachelor's degree in STEM (e.g., Science, Technology, Engineering, Mathematics, Statistics, Data Science, Economics).
* ** Work Experience**: 1 year or above, intern / co-op experience in analytical fields is counted.

** Why join us
*** Anti-Money Laundering (AML) is TD Bank's current top one priority. Support the bank's one of the most essential objectives through a high-impact analytical initiative with visibility across…