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.