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

We are seeking an exceptional Applied Scientist, Seller Abuse Prevention, to lead the development and implementation of advanced AI solutions that will transform how we prevent bad actors from operating in our store and enable Selling Partners to start and grow their business without fear of disruption, so that customers and Selling Partners across the globe trust us and have confidence in the integrity of Amazon's store. This role will focus 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.

Design and build predictive risk detection models using advanced AI techniques, including Natural Language Processing including 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