Commercial Abuse Analyst

• Investigate complex payment fraud, monetization abuse, account misuse, and commercial abuse schemes across Adobe's commerce ecosystem
• Analyze transactions, customer behaviors, payment activity, subscription usage, account relationships, and associated signals
• Identify suspicious patterns, assess risk exposure, determine root cause, and recommend mitigation, enforcement, or policy actions
• Evaluate escalations, emerging threat patterns, and high-risk activity to develop risk assessments and response recommendations
• Use SQL, analytical tools, and investigative methodologies to identify trends, uncover fraud patterns, validate hypotheses, and generate actionable intelligence
• Translate investigative findings into scalable detection strategies, risk signals, decisioning logic, and operational controls
• Partner with Data Science, Engineering, and AI teams to define abuse indicators, improve model performance, and enhance detection capabilities
• Produce intelligence assessments, trend analyses, and strategic insights on emerging abuse patterns, monetization risks, and evolving fraud trends
• Balance fraud prevention objectives with customer experience when evaluating controls, policies, detection strategies, and enforcement actions
• Recommend stronger payment risk controls, fraud mitigation strategies, automation opportunities, and long-term commerce risk initiatives
• Collaborate with Product, Commerce, Risk, Customer Support, Trust & Safety, and Engineering teams to address emerging threats and drive sustainable risk reduction

• Exceptional written and verbal communication skills
• Strong analytical and investigative skills
• Experience using SQL/SPL and data analysis techniques
• Strong understanding of payment and commerce risk concepts, including chargebacks, friendly fraud, account abuse, refund abuse, affiliate abuse, subscription fraud, identity risk, monetization abuse, and common payment ecosystem risks
• Experience identifying risk signals, anomalous behaviors, and abuse patterns and translating findings into scalable detection, mitigation, or enforcement strategies
• Creative and strategic problem-solving capabilities
• Ability to manage competing priorities and adapt quickly in a dynamic, fast-paced environment
• Self-motivated, proactive, and comfortable operating with ambiguity while working independently and collaboratively across cross-functional teams
• Strong attention to detail, sound judgment, and commitment to thorough, accurate, and high-confidence investigative outcomes
• Experience in payments risk, commerce fraud, fraud investigations, abuse prevention, trust and safety operations, fraud analytics, cybersecurity investigations, threat intelligence, or enterprise risk management is preferred
• Familiarity with machine learning concepts, risk models, AI-driven abuse trends, or applying AI and automation to fraud detection and investigative workflows is a plus
• Ability to balance fraud prevention objectives with customer experience, operational efficiency, and business outcomes

Demonstrates expertise in analyzing payment fraud and risk within commerce ecosystems, utilizing SQL and analytical tools to identify trends and develop scalable detection strategies. Capable of translating investigative findings into actionable intelligence while balancing fraud prevention with customer experience.

• SQL Data Analysis
• Fraud Investigation
• Risk Assessment
• Payment Risk Concepts
• Analytical Problem-Solving

• SQL
• Data Analysis Techniques
• Fraud Analytics
• Investigative Methodologies
• Risk Signals Identification
• Chargebacks
• Subscription Fraud
• Identity Risk
• Monetization Abuse
• Threat Intelligence

• Exceptional Communication Skills
• Attention to Detail
• Creative Problem-Solving
• Adaptability
• Self-Motivated

• Commerce Fraud
• Abuse Prevention
• Trust & Safety Operations
• Enterprise Risk Management
• Cybersecurity Investigations

• Analytical Tools
• AI-Driven Detection
• Machine Learning Concepts