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 dataSupport data collection, integration,



and retention requirementsFormulate hypotheses from complex business problemsRecommend solutions based on business implicationsSupport analytics and artificial intelligence training toolsRequirements:
Five to seven years in Data Science and AnalyticsRelated post-secondary degree or equivalent combinationSQL, Python, and PySpark programming experienceStatistical analysis and forecasting expertiseFraud model experience for a large financial institutionCombine data preparation, fraud risk knowledge, and analytical modelling to support BMO’s financial crime solutions and business recommendations.
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📌 Financial Crime Data Science Engineer (Winnipeg)
🏢 BMO
📍 Winnipeg