Fraud Prevention Data Analyst
Duration: Not determined
Job Title: Fraud Prevention Data Analyst – Lead / Specialist
Location: Toronto, ON
Job Summary: We are seeking a highly skilled and experienced Fraud Prevention Data Analyst to join our team. The ideal candidate will have a strong background in data analysis, business analysis, and business systems analysis, with extensive experience in the banking, insurance, and capital markets sectors. The Fraud Prevention Data Analyst will be responsible for detecting and preventing fraudulent activities by analyzing customer transaction data, developing and implementing fraud detection strategies, and collaborating with various stakeholders to ensure data integrity and compliance with regulatory requirements.
Key Responsibilities:
• Analyze customer transaction data, credit facilities, and credit card usage to detect fraudulent or suspicious activities, aiding compliance and anti-money laundering (AML) efforts.
• Develop and implement fraud detection strategies and dashboards to monitor key performance indicators (KPIs) for fraud prevention.
• Collaborate with stakeholders to gather and translate business requirements into technical specifications supporting fraud prevention initiatives.
• Conduct data analysis, modeling, and governance documentation to support fraud detection and prevention efforts.
• Lead initiatives to enhance cross-functional data optimization, performance, data lineage, risk and control assessments, and implement best practices in data gap analysis, quality testing, and regulatory testimony.
• Ensure end-to-end data delivery by coordinating with business stakeholders and technical teams to meet project requirements.
• Develop and support real-time fraud detection systems, delivering innovative solutions in an Agile environment.
• Conduct UAT tracking, maintain proof-of-concept (POC) data models, and contribute to the creation of reports, epics, and detailed user stories.
• Participate in Agile ceremonies including sprint planning, retrospectives, and regression testing phases.
Qualifications:
• Bachelor's or Master's degree in Computer Applications, Business Administration, or a related field.
• Proven experience as a Data Analyst, Business Analyst, or Business Systems Analyst in the banking, insurance, or capital markets sectors.
• Proficient in data modeling, analysis, requirement gathering, programming, design, architecture, development, testing, implementation, and production support.
• Experience working with Python, SQL, ETL, QlikView, Power BI, Tableau, and other data analysis tools.
• Strong knowledge of databases such as Oracle, MS-SQL Server, Sybase, DB2, NoSQL, MySQL, and MongoDB.
• Familiarity with big data technologies including Hadoop, Spark, Kafka, and Elastic Search.
• Excellent communication and collaboration skills, with the ability to work effectively in an Agile team environment.
• Strong problem-solving skills and attention to detail.
Preferred Skills:
• Experience with fraud detection and prevention in the financial services industry.
• Knowledge of regulatory requirements and compliance standards related to fraud prevention and AML.
• Familiarity with data governance policies and data profiling processes.
• Experience with tools such as JIRA, Confluence, Visio, and Collibra.
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