Turn complex financial crime data into actionable insight as a hybrid Financial Crime Data Science Engineer at BMO. The workplace is 100 King Street West.

This Data Engineer chance combines data science, programming, and fraud risk analysis within Data Analytics & Reporting. You will work with data owners and external vendors to select source data, prepare datasets, and formulate data-driven hypotheses. Your recommendations will address fraud investigation, detection, prevention, and broader financial crime exposures.

Key Responsibilities:

- Work with data owners to identify suitable analytical data
- Support data collection, integration, and retention requirements
- Formulate hypotheses from complex business problems




- Recommend solutions based on business implications
- Support analytics and artificial intelligence training tools

Requirements:

- Five to seven years in Data Science and Analytics
- Related post-secondary degree or equivalent combination
- SQL, Python, and PySpark programming experience
- Statistical analysis and forecasting expertise
- Fraud model experience for a large financial institution

Combine data preparation, fraud risk knowledge, and analytical modelling to support BMO’s financial crime solutions and business recommendations.

📌 Financial Crime Data Science Engineer (Toronto)
🏢 BMO
📍 Toronto