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Connecting People. Uniting the World. There’s never been a more exciting time to join United Airlines! As a global company that operates in hundreds of locations around the world — with millions of customers and tens of thousands of employees — we have a unique responsibility to uplift and provide opportunities in the places where we work, live and fly.
We’re on a path to becoming the best airline in aviation history. Join our Cybersecurity and Digital Risk (CDR) team to help lead the industry in cyber safety, security and resilience. United's CDR team plays a critical role in protecting our operations by enabling secure and resilient systems, managing threats and vulnerabilities, and ensuring swift response and recovery. Our mission is to seamlessly embed cybersecurity and digital risk management into every aspect of our business. We help drive progress and growth through trusted digital solutions, safeguarding assets and empowering our team, all while promoting a cyber-safe and secure environment that supports resilient airline operations.
United offers a competitive benefits package aimed at keeping you happy, healthy, and well-traveled. From employee-run "Business Resource Group" communities to world-class benefits like parental leave, 401(k), and privileges like space-available travel, United is truly a one-of-a-kind place to work. Are you ready to travel the world and help us keep our airline cyber safe? Apply today!
Job Overview and Responsibilities
The 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
What’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
united:WHQ00027057https://careers.united.com/sitemap.xmlThis posting hasn't been probed by our closure verifier yet. Stream C runs on a rolling schedule against postings approaching the close-decision threshold.
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