We are looking for a Business Analytics/Data Analyst to support data-driven decision-making within a financial services environment in Toronto, Ontario. This Long-term Contract position will focus on uncovering fraud-related trends, improving analytical processes, and translating complex business needs into practical data solutions. The successful candidate will work across analytics, business analysis, and data engineering activities to strengthen operational insight and support effective risk management.

Responsibilities:
• Analyze banking and lending data to identify suspicious activity, emerging fraud patterns, and behavioural indicators that support stronger detection strategies.
• Build, refine, and maintain analytical datasets and data pipelines using SQL and big data tools such as Trino and Hive to support reporting and investigation needs.
• Partner with business stakeholders to gather requirements, document workflows, and map current processes related to branch and lending operations.
• Develop and enhance business rules and analytical logic that improve the identification of application fraud and other financial risks.
• Translate business objectives into clear data and reporting solutions that support operational teams and decision-makers.
• Contribute to project delivery activities within financial services technology initiatives, including planning, coordination, and change-related support where required.
• Apply banking knowledge to assess lending practices, underwriting considerations, and compliance-related data requirements in analysis work.
• Prepare insights, findings, and recommendations for stakeholders through clear documentation, reporting, and presentations.
• Strong experience in business analytics or data analysis within a banking or financial services setting.
• Hands-on proficiency with Microsoft SQL for data extraction, transformation, and analysis.
• Working knowledge of fraud analytics, including application fraud, behavioural analysis, or transaction risk monitoring.
• Experience with data engineering concepts, including the development of data pipelines and work with platforms such as Trino or Hive.
• Ability to perform requirements gathering, process mapping, and business workflow analysis with multiple stakeholder groups.
• Sound understanding of lending products, underwriting practices, and regulatory or compliance considerations within banking.
• Proven ability to contribute to project-based delivery work in technology or operational change environments.

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