Applied Scientist, Payments Team

- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Experience using Unix/Linux
- Experience in professional software development
- 3+ years of hands-on predictive modeling and large data analysis experience
- 3+ years of building machine learning models or developing algorithms for business application experience

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The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually
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 prediction, forecasting and optimization models that generate multi-billion dollar predictions of the highest level of visibility and importance for Amazon's Payments and Customer Experience. 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.
- Develop state of the art AI Agents that reduce operations across Payment teams.
- Lead research on customizing LLMs to incorporate payment context and reduce latency of LLM invocation, reduce hallucinations and compute while maintaining or increasing accuracy.
- 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.
- 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.