Fraud Data & Technology Analyst

Accountabilities:

• Build, automate, and maintain fraud KPIs, dashboards, and reports covering program performance, loss drivers, mitigation outcomes, and emerging fraud trends.
• Analyze large and complex fraud datasets and translate findings into actionable insights and recommendations for leadership, operations, and frontline teams.
• Conduct performance assessments, cost-benefit analyses, business cases, and industry research to support fraud strategy and continuous improvement.
• Support the administration, maintenance, optimization, testing, and performance monitoring of fraud-related applications, platforms, tools, and system enhancements.
• Coordinate technology testing, validation, implementation, troubleshooting, and issue resolution to ensure reliable fraud technology performance.
• Partner with internal technology teams, business stakeholders, and vendors on fraud technology initiatives while maintaining clear documentation of processes, workflows, and system functionality.
• Tune, calibrate, and optimize fraud detection rules, models, and decisioning strategies to improve detection effectiveness while balancing operational efficiency and customer experience.
• Evaluate rule and model performance through testing, alert reviews, and performance metrics, recommending improvements to fraud monitoring strategies and controls.
• Ensure the accuracy, integrity, reliability, and quality of data used for fraud reporting, analysis, and decision-making.
• Support data governance through data dictionaries, reporting methodologies, quality validation, issue identification, documentation, and adherence to reporting standards.
• Identify opportunities for process improvement, automation, and stronger fraud controls in collaboration with cross-functional stakeholders.
• Provide analytical expertise and support for fraud-related initiatives across Fraud Operations, Risk, Compliance, IT, and business teams.

Requirements:

• Bachelor’s degree or higher is preferred.
• At least 3 years of experience in fraud analytics, fraud technology, fraud operations, risk management, banking, or a related field.
• Hands-on experience working with fraud and/or banking platforms.
• Strong experience using SQL or similar tools to query and analyze large datasets.
• Experience with data visualization and reporting platforms such as Tableau, Power BI, or comparable tools.
• Knowledge of fraud typologies involving payments, digital identity, account takeover, and application fraud.
• Strong analytical and problem-solving abilities, with the capacity to identify trends, evaluate performance, and develop practical recommendations.
• Excellent written and verbal communication skills, with the ability to explain complex findings clearly to both technical and non-technical audiences.
• Demonstrated ability to collaborate effectively with cross-functional teams and external technology partners.
• Experience with machine learning concepts or collaboration with data science teams is preferred.
• Familiarity with process mapping for technical or operational workflows is an asset.
• Knowledge of APIs, system integrations, or cloud-based data environments is preferred.
• Strong attention to data quality, accuracy, documentation, and governance.
• Ability to work independently, manage multiple priorities, and adapt in a fast-paced fraud and risk environment.
• Ability to successfully complete required criminal background and credit checks.
• This is a full-time, non-remote position requiring flexibility to work evenings and weekends when needed.
• Up to 10% travel may be required.

Benefits:

• Competitive annual salary of $56,000–$74,000 USD.
• Full-time, exempt position.
• Opportunity to work at the intersection of fraud analytics, technology, data, and risk management.
• Direct exposure to fraud detection strategies, rules, models, and financial crime prevention initiatives.
• Opportunities to collaborate with cross-functional teams across technology, risk, compliance, operations, and business functions.
• Professional development through hands-on experience with fraud platforms, data analytics, visualization, and emerging technologies.
• Equal opportunity workplace with reasonable accommodations available for qualified individuals with disabilities.