Lieu de travail : Toronto, Ontario, Canada Horaire : 37.5 Secteur d’activité : Analyses, informations et intelligence artificielle Détails de la rémunération : $96,900 - $136,800 CAD La TD a à cœur d’offrir une rémunération juste et équitable à tous les collègues. Les occasions de croissance et le perfectionnement des compétences sont des caractéristiques essentielles de l’expérience collègue à la TD. Nos politiques et pratiques en matière de rémunération ont été conçues pour permettre aux collègues de progresser dans l’échelle salariale au fil du temps, à mesure qu’ils s’améliorent dans leurs fonctions. Le salaire de base offert peut varier en fonction des compétences et de l’expérience du candidat, de ses connaissances professionnelles, de son emplacement géographique et d’autres besoins particuliers du secteur et de l’entreprise. En tant que candidat, nous vous encourageons à poser des questions sur la rémunération et à avoir une conversation franche avec votre recruteur, qui pourra vous fournir des détails plus précis sur ce poste. Description du poste : R_ 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 current 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

📌 Data Scientist Iii (Financial Crimes Network Analytics) (Toronto)
🏢 TD Bank Group
📍 Toronto