Build advanced fraud models with machine learning and deep learning as a hybrid Machine Learning Fraud Model Engineer at BMO. Work from 100 King Street West. Within BMO’s Data Analytics & Reporting group, this role develops data and artificial intelligence products for financial crime management. You will apply algorithms, statistical analysis, forecasting, multivariate testing, and optimization to discover patterns and improve fraud detection. The position also connects technical findings with business needs through clear storytelling and recommendations. Key Responsibilities:
Apply advanced algorithms to create better prediction models Discover patterns across potentially large datasets Research practical solutions to financial crime exposures Develop data and artificial intelligence products Build relationships with internal and external stakeholders Requirements:
Five to seven years of relevant analytics experience Advanced quantitative degree or equivalent experience Experience with XGBoost, H2O, or SparkML packages Deep proficiency in quantitative and predictive analytics Fraud modelling experience within a large financial institution Bring advanced algorithms, deep learning, and statistical expertise to BMO’s fraud prediction and financial crime analytics work.
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Machine Learning Fraud Model Engineer in Toronto employer: BMO
BMO Financial Group is an exceptional employer, offering a dynamic work environment in the heart of Toronto where legal professionals can thrive. With a strong commitment to employee growth, BMO provides extensive training, mentorship, and opportunities for career advancement, all while fostering a culture of diversity and inclusion. Employees enjoy a comprehensive benefits package, including health insurance, tuition reimbursement, and retirement savings plans, making it a rewarding place to build a meaningful career.
