DescriptionJob Overview and ResponsibilitiesThe Analyst - Fraud Data provides fraud business intelligence, analysis and storytelling that explains how fraud affects customers, operations, revenue and enterprise risk. This role integrates operational data on fraud detected, prevented and realized to quantify exposure, control outcomes, customer friction and financial impact. The Analyst uses approved artificial intelligence and automation tools to accelerate analysis, identify patterns, summarize findings, develop reporting content and improve the productivity and consistency of recurring workflows, with appropriate human validation and data-governance controls. The individual in this position develops clear narratives, dashboards and executive insights that connect fraud trends to business priorities and support informed decisions across the enterprise.
Fraud Business Impact Intelligence:
- Integrate fraud detected, prevented and realized-loss data to explain the scale, drivers and business implications of fraud across products, channels and customer journeys
Executive Storytelling & Insights:
- Translate complex operational and analytical findings into clear narratives, presentations and recommendations tailored to senior leaders and business stakeholders; use approved AI tools to accelerate synthesis, drafting and audience-specific communication with human review
Operational Performance Reporting:
- Develop and maintain dashboards and scorecards covering fraud volumes, prevented loss, realized loss, recovery, customer friction, operational workload and control outcomes; automate recurring data preparation, quality checks and reporting workflows where appropriate
Trend & Root-Cause Analysis:
- Analyze shifts in fraud activity and operational results to identify material trends, root causes, emerging risks and changes in business exposure; use approved AI-assisted methods to accelerate exploration, pattern identification and summarization
Financial & Customer Impact Measurement:
- Quantify the revenue, loss, cost, customer and operational effects of fraud and fraud controls, including tradeoffs between risk reduction and customer experience
Data Quality, Reporting Governance & Responsible AI:
- Establish consistent definitions, validation checks, documentation and reconciliation practices for fraud performance metrics, reporting datasets and AI-assisted outputs; protect sensitive data and validate accuracy, bias and business context
Cross-Functional Business Partnership:
- Partner with Fraud Strategy, Operations, Loyalty,
- Digital Technology, Customer Insights, Sales and other teams to align metrics, interpret results and turn insights into action
QualificationsWhat's needed to succeed (Minimum Qualifications):- Bachelor's degree. with preference for Business Analytics, Data Analytics, Finance, Economics, Statistics, Information Systems or a related quantitative or business field; equivalent experience accepted
- 2+ years of relevant experience in fraud analytics, business intelligence, operational analytics, financial analysis, risk analytics, ECDLP or a related discipline
- Demonstrated ability to quantify business impact, create clear data visualizations and translate analytical findings into concise recommendations for technical and non-technical audiences
- Ability to use approved generative AI and automation tools to improve analytical, reporting and documentation productivity while validating outputs
- SQL proficiency and experience reconciling, analyzing and interpreting large operational datasets
- Must be legally authorized to work in the United States for any employer without sponsorship
- Successful completion of interview required to meet job qualification
- Reliable, punctual attendance is an essential function of the position
What will help you propel from the pack (Preferred Qualifications):- Master's degree
- Business Analytics, Data Analytics, Finance, Economics or a related discipline
- Developing executive-ready reporting, presentations and narratives for senior business stakeholders
- Experience with fraud, retail, e-commerce, airline, financial services or another high-volume customer environment
- Knowledge of fraud operations, loss prevention, customer experience metrics, financial measurement or operational performance management; experience with enterprise AI assistants, natural-language analytics or workflow automation
- Tableau, Power BI, Looker or comparable visualization and reporting platform experience
Post Expiration 11/26/2026
