Develop fraud detection models with Python and SQL as a Data Scientist II at TD in Montréal, Quebec, Canada. Work 37.5 hours weekly.
This hands-on Data Scientist II role covers internal fraud and authentication models. You will apply machine learning, statistical analysis, feature engineering, and data visualization across the model development lifecycle. The work supports scalable analytical solutions for risk use cases.
Key Responsibilities: Develop and optimize models for fraud detection and authentication
Discover data and engineer features for model experimentation
Evaluate performance using fraud and risk metrics
Build documented workflows with Python, SQL, and data platforms
Monitor stability, performance, data gaps, and remediation actions




Requirements: Degree in a quantitative field such as Data Science or Statistics
Three to five-plus years in data science or machine learning
Proficiency in Python, SQL, statistical analysis, and machine learning
Experience developing predictive models in business or production environments
Solid presentation, writing, and stakeholder management skills
Apply fraud analytics, predictive modeling, Python, and SQL to strengthen TD’s internal risk capabilities in Montréal.

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📌 Fraud Detection Data Scientist II (Quebec City)
🏢 The Toronto-Dominion Bank (Canada)
📍 Quebec City