Overview: The Seller Lifecycle Management (SLM) team within Selling Partner Identity Verification (SPIV) focuses on knowing who we're doing business with at every stage of the selling lifecycle, from registering to sell in Amazon's store through any significant changes that impact selling accounts. The Program Manager will be responsible for ensuring that every selling account is operated by a verified and authenticated identity at every stage of the selling lifecycle. They are responsible for independently executing the overall program strategy across four major verticals in the organization: 1) strengthening identity change detection and preventing identity fraud 2) periodic re-verification of selling accounts across the lifecycle 3) applying selling account capability restrictions on bad actors 4) Driving process improvements on how we detect sellers
Key job responsibilities The SLM team is seeking an exceptional Risk Specialist to focus on identifying and disrupting sophisticated tax fraud schemes across Amazon's marketplace. This role sits at the critical intersection of tax compliance, fraudulent identity detection, and product innovation, with direct visibility to senior leadership as we transform Amazon's approach from reactive compliance to proactive risk intelligence.
Own end-to-end fraud investigations from initial detection through enforcement action, with explicit focus on extracting generalizable patterns that can be automated
Analyze every investigation through the lens of "how do we prevent this at scale?"—identifying the technical controls, data signals, and model features that would have caught this earlier
Prepare detailed investigation reports that include both case-specific findings and broader pattern insights with specific recommendations for Product/Tech/Science teams
Work across investigators to establish tight feedback loops: weekly syncs with Science teams on model performance, bi-weekly reviews with Product on prevention features, monthly deep-dives with Tax on policy implications
Lead incident response for high-impact fraud events or escalations, coordinating cross-functional teams to contain exposure and rapidly deploy preventive measures
Key job responsibilities Key job responsibilities The SLM team is seeking an exceptional Risk Specialist to focus on identifying and disrupting sophisticated tax fraud schemes across Amazon's marketplace. This role sits at the critical intersection of tax compliance, fraudulent identity detection, and product innovation, with direct visibility to senior leadership as we transform Amazon's approach from reactive compliance to proactive risk intelligence.
Own end-to-end fraud investigations from initial detection through enforcement action, with explicit focus on extracting generalizable patterns that can be automated
Analyze every investigation through the lens of "how do we prevent this at scale?"—identifying the technical controls, data signals, and model features that would have caught this earlier
Prepare detailed investigation reports that include both case-specific findings and broader pattern insights with specific recommendations for Product/Tech/Science teams
Work across investigators to establish tight feedback loops: weekly syncs with Science teams on model performance, bi-weekly reviews with Product on prevention features, monthly deep-dives with Tax on policy implications
Lead incident response for high-impact fraud events or escalations, coordinating cross-functional teams to contain exposure and rapidly deploy preventive measures
A day in the life You will part of a team of investigators and analysts to detect, investigate, and prevent tax and fraud perpetrated by bad actors attempting to exploit marketplace facilitator models.
Identify emerging abuse patterns at their earliest stages—detecting signals before they scale into significant damage to Amazon or our customers
Own investigations into sophisticated tax evasion schemes including VAT fraud, shell company abuse, customs manipulation, and identity misrepresentation
Continuously contribute to the refinement of detection logic by feeding investigation learnings back to Science teams, ensuring models evolve faster than fraudster tactics
Champion a culture of continuous improvement where every investigation generates actionable intelligence that strengthens prevention and detection systems
Work with investigators on the team to build case study repositories and pattern libraries that enable rapid knowledge transfer across teams and accelerate response to new fraud vectors
Basic Qualifications
- Bachelor's degree
- 3+ years of experience in fraud investigation, risk management, abuse, or a related analytical field
- Experience leveraging data and technology to drive process improvements
- Strong analytical skills with the ability to identify patterns in datasets and translate findings into actionable recommendations
- Clear written and verbal communication skills, including experience preparing reports for cross-functional audiences
- Bachelor's degree in Accounting, Finance, Criminal Justice, Computer Science, or related field
Preferred Qualifications
- Experience working with or alongside machine learning or data science teams on fraud detection or risk scoring
- Technical proficiency with SQL, Python, or data analysis tools
- Background in e-commerce, marketplace platforms, or digital economy taxation
- Demonstrated ability to identify early-stage abuse patterns before they scale
- Certified Fraud Examiner (CFE), Certified Anti-Money Laundering Specialist (CAMS), or similar certification
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