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Amazon

Applied Scientist, Seller Fees Science

Amazon, Seattle, Washington, us, 98127

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Overview The Seller Fees organization drives the monetization infrastructure powering Amazon’s global marketplace, processing billions of transactions for over two million active third‑party sellers worldwide. Our team owns the complete technical stack and strategic vision for fee computation systems, leveraging advanced machine learning to optimize seller experiences and maintain fee integrity at unprecedented scale.

Key Responsibilities

Architect and deploy state‑of‑the‑art transformer‑based models for fee classification and anomaly detection across hundreds of millions of products

Pioneer novel applications of multimodal LLMs to analyze product attributes, images, and seller metadata for intelligent fee determination

Build production‑scale generative AI systems for fee integrity and seller communications

Advance the field of ML through novel research in high‑stakes, large‑scale transaction processing

Develop SOTA causal inference frameworks integrated with deep learning to understand fee impacts and optimize seller outcomes

Collaborate with world‑class scientists and engineers to solve complex problems at the intersection of deep learning, economics, and large business systems

Design measurable and scalable science solutions that can be adopted across stores worldwide with different languages, policy and requirements

Integrate AI (both generative and symbolic) into compound agentic workflows to transform complex business systems into intelligent ones for both internal and external customers

Develop large‑scale classification and prediction models using the rich features of text, image and customer interactions and state‑of‑the‑art techniques

Research and implement novel machine learning, statistical and econometrics approaches

Write high‑quality code and implement scalable models within the production systems

Stay up to date with relevant scientific publications

Collaborate with business and software teams both within and outside of the fees organization

About the Team The Seller Fees organization drives the monetization infrastructure powering Amazon’s global marketplace, processing billions of transactions for over two million active third‑party sellers worldwide. Our team owns the complete technical stack and strategic vision for fee computation systems, leveraging advanced machine learning to optimize seller experiences and maintain fee integrity at unprecedented scale.

Basic Qualifications

Experience programming in Java, C++, Python or related language

Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse

Preferred Qualifications

Experience implementing algorithms using both toolkits and self‑developed code

Have publications at top‑tier peer‑reviewed conferences or journals

Compensation Our compensation reflects the cost of labor across several U.S. geographic markets. The base pay for this position ranges from $129,400/year in our lowest geographic market up to $212,800/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job‑related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign‑on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.

EEO and Accommodations Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Posted Posted:

January 8, 2026 (Updated 1 day ago)

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