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# Catalog Specialist, RCX

- **Company:** Amazon.com, Inc.
- **Location:** Bellevue, WA, United States
- **Salary:** $44,886.0 - $63,898.0
- **Contract:** Permanent contract
- **Skills:** Microsoft Word, Microsoft Excel, Algorithm Design, Machine Learning, Microsoft Office, Microsoft PowerPoint
- **Published:** September 18, 2026
- **Apply:** https://dejobs.org/x/x/BF60AF8E85C541A49F32EECF4A64717A/job/

## About the Role

* Strong analytical skills and the ability to deep-dive on complex problems

 * Ability to manage multiple simultaneous projects requiring frequent communication, organization/time management and problem-solving skills, * Bachelor's degree
 * Speak, write, and read fluently in English
 * Experience with Microsoft Office products and applications
 * 1+ years of proven experience in data annotation and labeling for ML model training and evaluation., * Experience in natural language data labeling, data annotation, linguistic annotation or other forms of data markup, or experience with computer skills, including proficiency in MS Office (Word, Excel, PowerPoint)
 * Experience working on the MTurk or Sagemaker platform for data annotation tasks
 * Familiarity with Amazon's product and category ecosystem
 * Previous exposure to machine learning concepts and algorithms
 * Demonstrated ability to adapt to evolving technologies and methodologies in the ML domain

## Description

We are hiring an experienced Catalog Specialist to help us grow our business in innovative ways. In this role, you will work closely with our product, technology and science teams to support new Machine Learning (ML) models and data science classification algorithm development - all helping to delight our customers through new experiences throughout their Amazon shopping journey., * Work closely with our product, technology, and science teams to support Machine Learning (ML) models

 * Perform data annotation required to train and evaluate ML models effectively

 * Support data scientists in the development of classification algorithms

 * Collaborate with cross-functional teams to ensure data annotation tasks align with project objectives and timelines

 * Maintain high-quality standards for annotated data to optimize model performance

 * Continuously evaluate and improve annotation processes to enhance efficiency and accuracy


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