Build advanced fraud models with machine learning and deep learning as a hybrid Machine Learning Fraud Model Engineer at BMO. Work from 100 King Street West.

Within BMO’s Data Analytics & Reporting group, this role develops data and artificial intelligence products for financial crime management. You will apply algorithms, statistical analysis, forecasting, multivariate testing, and optimization to discover patterns and improve fraud detection. The position also connects technical findings with business needs through explicit storytelling and recommendations.

Key Responsibilities:

- Apply advanced algorithms to create better prediction models
- Discover patterns across potentially large datasets
- Research practical solutions to financial crime exposures




- Develop data and artificial intelligence products
- Build relationships with internal and external stakeholders

Requirements:

- Five to seven years of relevant analytics experience
- Advanced quantitative degree or equivalent experience
- Experience with XGBoost, H2O, or SparkML packages
- Deep proficiency in quantitative and predictive analytics
- Fraud modelling experience within a large financial institution

Bring advanced algorithms, deep learning, and statistical expertise to BMO’s fraud prediction and financial crime analytics work.

📌 Machine Learning Fraud Model Engineer (Toronto)
🏢 BMO
📍 Toronto