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 prospect 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.