Fraud Predictive Analytics Engineer (Hybrid)

Bank N.A.; Toronto; Hybrid; CAD 80,000 - 175,000; Full time

Benefits offered by this job

Health insurance

Tuition reimbursement

Life insurance

Retirement savings plan

Job summary

BMO Financial Group in Toronto seeks an experienced Data Scientist to apply advanced analytics, ML/DL and pattern detection to financial crime problems. You will build predictive models and dashboards, translate findings into actionable business insights, and collaborate across teams.

The role requires 5–7 years of data science experience, strong programming skills (SQL, Python, PySpark) and ML libraries. The position offers a hybrid work arrangement and a comprehensive benefits package.

Qualifications

• Typically 5–7 years of relevant experience in Data Science & Analytics or equivalent.
• Advanced degree in CS, Math, Physics, Engineering, Statistics, or related quantitative field.
• Experience with programming languages (SQL, Python, PySpark) and ML/DL libraries (XGBoost, H2O, SparkML).
• Deep proficiency in statistical analysis, forecasting and optimization algorithms.
• Experience building fraud models for a large financial institution.

Responsibilities

• Apply advanced analytic algorithms to deliver better prediction models and automation.
• Summarize findings and present actionable insights to business groups with strong storytelling.
• Develop data-driven hypotheses to drive business value and support data collection/retention needs.
• Build data solutions by leveraging pattern detection on large datasets from internal/external sources.
• Diagnose model performance issues and propose efficiency improvements.
• Collaborate with stakeholders to ensure alignment and transfer knowledge via training.

Skills

SQL

Python

PySpark

Statistical analysis

Predictive analytics

Storytelling / communication

Education

Post-secondary degree

Advanced degree

Tools

XGBoost

H2O

SparkML

Job description

BMO Financial Group in Toronto seeks an experienced Data Scientist to apply advanced analytics, ML/DL and pattern detection to financial crime problems. You will build predictive models and dashboards, translate findings into actionable business insights, and collaborate across teams.

The role requires 5–7 years of data science experience, strong programming skills (SQL, Python, PySpark) and ML libraries. The position offers a hybrid work arrangement and a comprehensive benefits package.