Data Scientist II, Anti Money Laundering Transaction Monitoring

BMO Financial Group is seeking a Data Scientist II to advance its AML transaction monitoring program from the Chicago area. The role centers on the design, development, and deployment of machine learning and analytical models for detecting money laundering activity and supporting the model lifecycle, with collaboration across AML Compliance, investigations, governance, and technology teams.

Responsibilities

• Design, build, test, and deploy machine learning and analytical models used for AML transaction monitoring and suspicious activity detection
• Analyze large volumes of customer, transactional, payment, and alert data to identify emerging money laundering risks, typologies, and anomalous behavior patterns
• Develop and evaluate supervised and unsupervised machine learning approaches to improve detection effectiveness and investigator outcomes
• Conduct feature engineering and exploratory data analysis to identify behavioral indicators associated with financial crime risk
• Perform quantitative assessments of model performance, including detection effectiveness, productivity, false positive reduction, and risk coverage
• Support model tuning, optimization, and revalidation activities to ensure models continue to perform as intended
• Assess data quality and data lineage and partner with data management teams to resolve issues affecting model performance and reliability
• Prepare clear and comprehensive model development, testing, and governance documentation to support model validation, audit, and regulatory reviews
• Translate analytical findings into actionable recommendations for AML Compliance, FIU, and senior management
• Collaborate with business stakeholders, investigators, model governance, and technology partners to prioritize enhancements and implement solutions
• Research emerging financial crime typologies, machine learning techniques, and industry best practices to continuously improve monitoring capabilities
• Contribute to strategic initiatives involving AI, machine learning, graph analytics, network analysis, and other advanced analytical approaches applicable to financial crime detection
• Ensure all analysis and model development activities comply with regulatory requirements, internal policies, and model risk management standards
• Take measured risks while protecting the bank by applying the Risk Management Framework and exercising sound risk-based judgment

Requirements

• Typically between 4 - 6 years of relevant experience and a post-secondary degree in a related field or an equivalent combination of education and experience
• Experience with Python and SQL for large-scale data analysis, feature engineering, and model development
• Strong understanding of statistical analysis, machine learning algorithms, and model performance measurement
• Experience working with large structured and semi-structured datasets
• Experience using version control tools and code repositories (e.g., Git, GitHub, Azure DevOps) to support collaborative development and reproducible analytical workflows
• Familiarity with generative AI tools and AI-assisted development practices (e.g., Microsoft 365 Copilot, GitHub Copilot, LLM-based coding assistants) to improve productivity, documentation, and analytical workflows
• Ability to communicate technical concepts effectively to both technical and non-technical audiences

Technologies

• Python
• SQL
• Git
• GitHub
• Azure DevOps
• Dataiku
• Databricks
• SAS
• Spark
• Hadoop
• Microsoft 365 Copilot
• GitHub Copilot
• LLM-based coding assistants
• Cloud-based analytics platforms

Benefits

• Performance-based incentives
• Discretionary bonuses
• Health insurance
• Tuition reimbursement
• Accident and life insurance
• Retirement savings plans

Application deadline

08/04/2026

Location

Chicago, IL (onsite)

Address

320 S Canal Street

Salary

USD 69,000 - 127,800 per year — Salaried

Job Family Group

Data Analytics & Reporting