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Description

Are you passionate about applying machine learning and advanced statistical techniques to protect one of the world's largest online marketplaces? Do you want to be at the forefront of developing innovative solutions that safeguard Amazon's customers and legitimate sellers while ensuring a fair and trusted shopping experience? Do you thrive in a collaborative environment where diverse perspectives drive breakthrough solutions?

If yes, we invite you to join the Amazon Risk Intelligence Science Team. We're seeking an exceptional scientist who can revolutionize how we protect our marketplace through intelligent automation. As a key member of our team, you'll develop and deploy state-of-the-art machine learning systems that analyze millions of seller interactions daily, ensuring the integrity and trustworthiness of Amazon's marketplace while scaling our operations to new heights. Your work will directly impact the safety and security of the shopping experience for hundreds of millions of customers worldwide, while supporting the growth of honest entrepreneurs and businesses.

Key job responsibilities
• Use machine learning and statistical techniques to create scalable abuse detection solutions that identify fraudulent seller behavior, account takeovers, and marketplace manipulation schemes

• Innovate with the latest GenAI technology to build highly automated solutions for efficient seller verification, transaction monitoring, and risk assessment

• Design, develop and deploy end-to-end machine learning solutions in the Amazon production environment to prevent and detect sophisticated abuse patterns across the marketplace

• Learn, explore and experiment with the latest machine learning advancements to protect customer trust and maintain marketplace integrity while supporting legitimate selling partners

• Collaborate with cross-functional teams to develop comprehensive risk models that can adapt to evolving abuse patterns and emerging threats

About the team
You'll be working closely with business partners and engineering teams to create end-to-end scalable machine learning solutions that address real-world problems. You will build scalable, efficient, and automated processes for large-scale data analyses, model development, model validation, and model implementation.

You will also be providing clear and compelling reports for your solutions and contributing to the ongoing innovation and knowledge-sharing that are central to the team's success.