Sr. Applied Scientist, Amazon B2b Payments and Lending, Credit and Fraud Science

Amazon Amazon · Big Tech · NY +1 · Applied Science

Senior Applied Scientist role focused on applying AI/ML and GenAI to credit management, B2B financial services, and payments within Amazon. The role involves developing and deploying production models for credit and fraud management, enhancing product features, and leveraging alternative data. It requires experience with foundation models, agentic frameworks, and LLM-powered automation, with a strong emphasis on operational excellence and delivering customer value through AI-driven insights and automation.

What you'd actually do

  1. Understand business and product strategies, goals and objectives. Make recommendations for new techniques/strategies including GenAI innovations, agentic AI frameworks, and foundation models, and to improve customer experience and business outcomes
  2. Apply advanced data mining, machine learning, and Generative AI techniques to create AI/ML capabilities and support Credit and Fraud Management
  3. Source, incorporate, and analyze alternative data to drive innovation, utilizing GenAI and foundation models
  4. Own production models (real time and batch), conduct code review and model monitoring to insist high bar of operating excellence and ensure high performant models
  5. Conduct research and educate business, product, marketing and product teams on the implementation of models and GenAI innovations, enabling strategic decision making through AI-powered insights and automation

Skills

Required

  • Python
  • SQL
  • AWS
  • Machine Learning
  • Generative AI
  • Data Mining
  • Credit Management
  • Fraud Management
  • Quantitative field degree (Master's or equivalent)

Nice to have

  • Ph.D. in a quantitative field
  • AI-native systems design and deployment
  • Foundation models
  • Agentic frameworks
  • LLM-powered automation
  • Leading scientists
  • Developing junior members
  • Credit underwriting experience
  • Financial services domain experience
  • Project management
  • Long-term research vision development

What the JD emphasized

  • production models
  • GenAI innovations
  • agentic AI frameworks
  • foundation models
  • AI/ML capabilities

Other signals

  • Apply advanced data mining, machine learning, and Generative AI techniques to create AI/ML capabilities and support Credit and Fraud Management
  • Own production models (real time and batch), conduct code review and model monitoring to insist high bar of operating excellence and ensure high performant models
  • Experience designing and deploying AI-native systems that leverage foundation models, agentic frameworks, and LLM-powered automation