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Applied Scientist III, Buyer Risk Prevention

Amazon

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Location:
India , Bengaluru

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Contract Type:
Not provided

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Salary:

Not provided

Job Description:

Do you want to lead the development of advanced machine learning systems that protect millions of customers and power a trusted global eCommerce experience? Are you passionate about modeling terabytes of data, solving highly ambiguous fraud and risk challenges, and driving step-change improvements through scientific innovation? If so, the Amazon Buyer Risk Prevention (BRP) Machine Learning team may be the right place for you. We are seeking a Senior Applied Scientist to define and drive the scientific direction of large-scale risk management systems that safeguard millions of transactions every day. In this role, you will lead the design and deployment of advanced machine learning solutions, influence cross-team technical strategy, and leverage emerging technologies—including Generative AI and LLMs—to build next-generation risk prevention platforms.

Job Responsibility:

  • Lead the end-to-end scientific strategy for large-scale fraud and risk modeling initiatives
  • Define problem statements, success metrics, and long-term modeling roadmaps in partnership with business and engineering leaders
  • Design, develop, and deploy highly scalable machine learning systems in real-time production environments
  • Drive innovation using advanced ML, deep learning, and GenAI/LLM technologies to automate and transform risk evaluation
  • Influence system architecture and partner with engineering teams to ensure robust, scalable implementations
  • Establish best practices for experimentation, model validation, monitoring, and lifecycle management
  • Mentor and raise the technical bar for junior scientists through reviews, technical guidance, and thought leadership
  • Communicate complex scientific insights clearly to senior leadership and cross-functional stakeholders
  • Identify emerging scientific trends and translate them into impactful production solutions

Requirements:

  • 3+ years of building machine learning models for business application experience
  • PhD, or Master's degree and 6+ years of applied research experience
  • Experience programming in Java, C++, Python or related language
  • Experience with neural deep learning methods and machine learning

Nice to have:

  • Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
  • Experience with large scale distributed systems such as Hadoop, Spark etc.
  • Have publications at top-tier peer-reviewed conferences or journals

Additional Information:

Job Posted:
March 20, 2026

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