Applied Scientist I, Amazon Payments Team

Amazon Payments build systems that process payments at an unprecedented scale, with accuracy, speed, and mission-critical availability. We process millions of transactions every day worldwide across various payment methods. Over 100 million customers and merchants send hundreds of billions of dollars moving at light-speed through our systems annually. We are looking for a highly skilled, experienced, and motivated Applied Scientist to innovate and solve complex scientific optimization challenges at a massive scale.

This Applied Scientist role will design and implement state-of-the-art AI optimization models that generate multi-billion dollar predictions of the highest level of visibility and importance for Amazon's Payments and Customer Experience. The scientist will work on implementing Agentic workflows within production systems that will tremendously improve developer productivity at scale. A successful candidate will be a problem solver who enjoys diving into data, is excited by difficult modeling challenges, and possesses strong communication skills to effectively interface between technical and business teams. You will contribute to the research community by working with other scientists across Amazon and our Payments Engineering as well as by collaborating with academic researchers and publishing papers. You will work closely with Software Development Engineers to invent and construct models on data at massive scale and it is likely that your work will end up in an Amazon product. Finally, you will also have exposure to senior leadership as we communicate results and provide scientific guidance to the business.



Key job responsibilities
As a Applied Scientist you will:
- Drive collaborative research and creative problem solving.
- Write production-grade quality code for deploying machine learning and deep learning modes.
- Constructively critique peer research and mentor junior scientists and engineers.
- Create experiments and prototype implementations of state-of-the-art AI techniques.
- Create agentic workflows using GenAI state-of-the-art techniques.
- Collaborate with engineering teams to design and implement software solutions for science problems.
- Contribute to progress of the Amazon and broader research communities by producing publication
- Effectively collaborate in a fast paced environment with multiple teams in large organization (software development, Project Management, Build and Release, etc).


About the team
Amazon Payments Machine Learning team leverages data across the payment lifecycle to build ML capabilities to improve payment-operations' success rates for verification, authentication, authorization, settlement, refund, disbursement etc. The team also leads impactful generative AI initiatives, driving reductions in operations, an improved developer experience, and friction-less client interactions.