Catalog Specialist RCX
Catalog Specialist RCX
Posted on :
27-04-2025
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1 Vacancy
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Job Description
In the Worldwide Returns ReCommerce & Sustainability (WW RR&S) group at Amazon we are dedicated to making zero happen zero cost of returns zero waste and zero defects to benefit our customers company and environment. We are an agile and inclusive organization that constantly innovates to create longterm value by investing in our people and our planet not simply focusing on the bottom line.
WW R&R includes business product operations data and software engineering teams who together manage the lifecycle of returned and damaged products. In WW R&R you will partner across these teams to help customers discover great deals on quality used rentals and open box items; get the most value out of Amazons products; improve the customer returns experience; and reduce defects waste and cost in reverse logistics processes. You will be a leader a builder and an owner collaborating crossfunctionally with technical operations and business teams to design scalable and automated solutions to customer problems.
Amazon is Earths most customercentric company and in WW R&R the Earth is our customer too. Come join us and innovate with the Amazon Worldwide Returns ReCommerce & Sustainability team!
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.
Key job responsibilities
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 crossfunctional teams to ensure data annotation tasks align with project objectives and timelines
Maintain highquality standards for annotated data to optimize model performance
Continuously evaluate and improve annotation processes to enhance efficiency and accuracy
Strong analytical skills and the ability to deepdive on complex problems
Ability to manage multiple simultaneous projects requiring frequent communication organization/time management and problemsolving skills
Bachelors 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 working on the MTurk or Sagemaker platform for data annotation tasks
Proven experience in data annotation and labeling for ML model training and evaluation
Understanding of data annotation methodologies and tools
Familiarity with Amazons 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
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 for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $32900/year in our lowest geographic market up to $70300/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on jobrelated knowledge skills and experience. Amazon is a total compensation company. Dependent on the position offered equity signon 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. For more information please visit This position will remain posted until filled. Applicants should apply via our internal or external career site.
WW R&R includes business product operations data and software engineering teams who together manage the lifecycle of returned and damaged products. In WW R&R you will partner across these teams to help customers discover great deals on quality used rentals and open box items; get the most value out of Amazons products; improve the customer returns experience; and reduce defects waste and cost in reverse logistics processes. You will be a leader a builder and an owner collaborating crossfunctionally with technical operations and business teams to design scalable and automated solutions to customer problems.
Amazon is Earths most customercentric company and in WW R&R the Earth is our customer too. Come join us and innovate with the Amazon Worldwide Returns ReCommerce & Sustainability team!
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.
Key job responsibilities
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 crossfunctional teams to ensure data annotation tasks align with project objectives and timelines
Maintain highquality standards for annotated data to optimize model performance
Continuously evaluate and improve annotation processes to enhance efficiency and accuracy
Strong analytical skills and the ability to deepdive on complex problems
Ability to manage multiple simultaneous projects requiring frequent communication organization/time management and problemsolving skills
Bachelors 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 working on the MTurk or Sagemaker platform for data annotation tasks
Proven experience in data annotation and labeling for ML model training and evaluation
Understanding of data annotation methodologies and tools
Familiarity with Amazons 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
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 for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $32900/year in our lowest geographic market up to $70300/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on jobrelated knowledge skills and experience. Amazon is a total compensation company. Dependent on the position offered equity signon 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. For more information please visit This position will remain posted until filled. Applicants should apply via our internal or external career site.
Required Experience:
Unclear Seniority
Employment Type
Full-Time
Key Skills
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