Apply machine learning and predictive analytics as a hybrid Fraud Analytics Data Engineer at BMO, based at 100 King Street West. Build models that support smarter decisions and fraud controls.

This Data Engineer role sits within Data Analytics & Reporting and focuses on financial crimes. You will develop analytical solutions using statistical methods, artificial intelligence, deep learning, and programming. Your work will support fraud detection, investigation, prevention, and intelligent automation across the Financial Crimes Unit.

Key Responsibilities:

- Develop fraud detection, investigation, and prevention tools and models
- Assemble structured, semi-structured, and unstructured source data
- Apply machine learning techniques to test and refine hypotheses




- Diagnose predictive model performance issues and improve efficiency
- Present statistical findings and actionable business insights

Requirements:

- Five to seven years of relevant Data Science and Analytics experience
- Post-secondary degree or equivalent education and experience
- Programming experience with SQL, Python, and PySpark
- Proficiency in statistical and predictive analytics
- Experience building fraud models for a large financial institution

Use Python, predictive analytics, and fraud modelling expertise to develop practical financial crimes solutions at BMO.

📌 Fraud Analytics Data Engineer (Toronto)
🏢 BMO
📍 Toronto