AML Developer

Job summary

Maintain and tune AML/ATF transaction monitoring scenarios, analytical queries, and machine learning models, while supporting performance monitoring and audit-ready documentation. Partner with FCRM and business teams to resolve monitoring issues, identify improvements, and develop data-driven solutions that mitigate money laundering and terrorist financing risks.

Job details

AML Developer IV Location: Toronto, ON Onsite Flexibility: Hybrid — 3 days in office, 2 days work from home (could potentially go to 4 days in office) Contract Details Position Type: Contract Contract Duration: 6 months (with possibility of extension and conversion based on business needs and performance) Pay Rate: C$85.00–C$103.00 / Hour (CAD) Shift / Schedule: Monday–Friday, core business hours, 37.5 hours per week, 7.5 hours per day Travel Requirements: Not required Job Summary Reporting to the Senior Advanced Analytics Manager, the Data Scientist will be conducting all analytical activities related to FCRM transaction monitoring systems. The scope of the project encompasses data science initiatives focused on enhancing operational efficiencies, adding risk elements to investigation, and adding models and rules for monitoring requirements, including data analysis and model development. The team consists of 16 people and operates in a very collaborative culture. This is a senior lead role requiring the ability to work independently, manage and direct activities related to analysis, design, and support of technical data management solutions on various projects ranging in complexity and size. The contractor will have access to customer data. TD onboarding and knowledge transfer will be provided during the training period. Key Responsibilities Provide maintenance of transaction monitoring scenarios, and analytical queries in support of the bank's strategic efforts to mitigate money laundering and terrorist financing risk Conduct activities related to AML/ATF scenario performance tuning, machine learning execution and model performance monitoring Help maintain a structured documentation process to demonstrate an effective scenario review program to satisfy audit, compliance, and regulatory requirements With assistance from management, assist with transaction monitoring related issues/questions from Global AML members, audit, and other partners Provide analytical thought leadership and stay ahead of developments in data mining and the application of data science Partner with FCRM teams to implement changes to existing solutions and/or the implementation of alternative solutions and serve as an ambassador for data science Use statistical and machine learning techniques to build and maintain effective and efficient transaction monitoring, customer behavior, and risk scoring models Provide insight into leading analytic practices, design and lead iterative learning and development cycles, and ultimately produce new and creative analytic solutions that will become core work Act as enterprise or functional expert, requiring broad managerial and deep specialized knowledge at the enterprise, business, regulatory and industry levels Work with various business teams to help identify areas for improvement and provide insights using supporting data and models to support business strategies Required Skills Extensive work experience building predictive models with machine learning methods Expert knowledge of Python, PySpark, Databricks, Azure, and SQL Expert data exploration and analysis skills Ability to apply statistical techniques and data mining tools to solve business problems Strong communication skills (written and verbal) Strong interpersonal skills Self-motivated, well organized, able to work both independently and in a team environment Attention to detail; self-starter and adaptable Preferred Skills Any Databricks, programming, or statistics certifications Java, Scala, Tableau AML knowledge and experience on data-driven or data-centered projects Banking or financial institution experience Education Requirements Bachelor's degree or higher in Statistics, Computer Science/Software Engineering required Master's degree preferred Databricks, programming, or statistics certifications are an asset Required Experience 8 years of overall experience Work Environment / Physical Requirements Anchor days: Markham – Monday; Toronto – Wednesday Approximately 2 hours per day spent in meetings on average All interactions are internal to the organization About the Client This client is a leading financial services and banking institution, headquartered in Toronto, Ontario, and recognized as one of North America's largest financial institutions — the sixth-largest bank on the continent by branches — serving approximately 22 million customers across Canada, the United States, Europe, and the Asia-Pacific region. With a team of over 85,000 employees worldwide, the organization operates a full-service financial platform spanning personal and commercial banking, wealth management, insurance, and payment solutions. Teams here include retail banking advisors, commercial lenders, wealth management professionals, risk analysts, and technology specialists — including data scientists, AML developers, and IT professionals who collaborate in fast-paced, team-oriented environments built around long-term career development and inclusion. About GTT GTT is a minority-owned staffing firm and a subsidiary of Chenega Corporation, a Native American-owned company in Alaska. We highly value diverse and inclusive workplaces and support Fortune 500 organizations across banking, financial services, technology, life sciences, biotech, utilities, and retail sectors throughout the U.S. and Canada. Job Number: 26-15988 Industry: Software Engineering #gttca

What you’ll do

Maintain and tune AML/ATF transaction monitoring scenarios, analytical queries, and machine learning models, while supporting performance monitoring and audit-ready documentation. Partner with FCRM and business teams to resolve monitoring issues, identify improvements, and develop data-driven solutions that mitigate money laundering and terrorist financing risks.

Requirements

Requires at least 8 years of overall experience, extensive experience building predictive machine learning models, and expert knowledge of Python, PySpark, Databricks, Azure, and SQL. A bachelor's degree or higher in Statistics, Computer Science, or Software Engineering is required; a master's degree is preferred, and banking or AML experience is an asset.

Listed skills

• Machine learning · Preferred
• Python · Preferred
• Microsoft Azure · Preferred
• SQL · Preferred
• transaction monitoring · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Machine Learning
• Predictive Modeling
• Python
• PySpark
• Databricks
• Azure
• SQL
• Statistical Analysis
• Data Exploration
• Data Mining
• Transaction Monitoring
• AML/ATF
• Model Performance Monitoring
• Risk Scoring
• Analytical Communication

Job areas

• Data & Analytics
• Technology
• Software
• Finance & Accounting
• Science & Research

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