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
- Strong presentation, writing, and stakeholder management skills
Apply fraud analytics, predictive modeling, Python, and SQL to strengthen TD's internal risk capabilities in Montréal.
Fraud Detection Data Scientist II in Montréal employer: TD Bank Group
TD Bank Group is an exceptional employer that fosters a collaborative and innovative work culture, particularly in the dynamic field of Payments Modernization. Employees benefit from comprehensive professional development opportunities, competitive compensation, and a commitment to work-life balance, all while being part of a leading financial institution located in the vibrant city of Toronto.
