Applied Scientist, Global Risk Intelligence and Prevention, Seller Abuse Prevention

About the role

We are seeking an exceptional Applied Scientist to lead the development and implementation of advanced AI solutions that will transform how we prevent bad actors from operating in our store. This role focuses on building risk detection models leveraging state-of-the-art AI, including small language models, to detect and prevent abuse of Amazon's catalog worldwide. You will design, develop, and deploy scalable AI solutions to proactively detect and prevent marketplace abuse throughout the seller lifecycle.

Responsibilities

• Design and build predictive risk detection models using advanced AI techniques, including Natural Language Processing, LLMs, and agents to proactively identify bad actors and prevent marketplace abuse at scale.
• Own the end-to-end scientific solution from risk quantification through decision optimization, determining the appropriate actions to take across varying risk levels.
• Develop interpretability and reasoning pipelines that provide transparent, actionable explanations for model decisions to support enforcement and seller experience.
• Work with risk programs across the seller lifecycle to define detection strategies, translate operational investigation patterns into automated systems, and prioritize high-impact risk areas.
• Partner with engineering teams to deploy models into production, define evaluation frameworks, and collaborate with operations and verification teams to measure and improve detection effectiveness.
• Explore datasets to understand predictors and patterns of abuse.
• Work with product, program, and engineering stakeholders to build solutions into production that will last.
• Identify new and emerging abuse vectors as abusers get more sophisticated.
• Use search, graph, computer vision, NLP, and anomaly detection methodologies to automatically detect abusive actions.

A day in the life

• Explore datasets to understand predictors and patterns of abuse.
• Work with product, program, and engineering stakeholders to build solutions into production that will last.
• Identify new and emerging abuse vectors as abusers get more sophisticated.
• Use search, graph, computer vision, NLP, and anomaly detection methodologies to automatically detect abusive actions.

About the team

Seller Abuse Prevention detects abuse across 4 distinct spaces: catalog, review, financial risk, and discovery/competitor abuse. The team is embedded in a group of scientists tackling cross-spanning risk prevention problems, with expertise in graph networks, LLMs/agents, and fraud detection.

Qualifications

Basic Qualifications

• PhD, or Master's degree and 4+ years of CS, CE, ML, or related field experience.
• Experience programming in Java, C++, Python, or related language.
• Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing.

Preferred Qualifications

• Experience using Unix/Linux.
• Experience in professional software development.

Pay

Base salary range: $142,800.00 - $193,200.00 USD annually (Seattle, WA). Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on experience, qualifications, and location.

Benefits

• Comprehensive health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance, and optional supplemental life plans).
• Employee Assistance Program (EAP) and mental health support.
• Medical Advice Line and Flexible Spending Accounts.
• Adoption and surrogacy reimbursement coverage.
• 401(k) matching.
• Paid time off and parental leave.

Learn more about our benefits at amazon.jobs/en/benefits.