Amazon.com Services LLC

Project/Program/Product Management--Non-Tech, Catalog, transportation and logistics

CatalogSpecialist

$0–0k Bellevue, Washington, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“Catalog Specialist at Amazon.com Services LLC. Skills: Data annotation, ML models, Classification algorithms. Support Machine Learning (ML) models. Perform data annotation”

What You'll Achieve.

Optimize model performance; Enhance efficiency and accuracy

Industry & Context.

Project/Program/Product Management Non Tech, Catalog, transportation and logistics
Problems you'll solve

Deep-dive on complex problems

What They're Looking For.

Must Have

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

Nice to Have

Experience in natural language data labeling, Experience in data annotation, Experience in linguistic annotation, Experience in other forms of data markup, Experience working on the MTurk platform, Experience working on the Sagemaker platform, Understanding of data annotation methodologies, Understanding of data annotation tools, Familiarity with Amazon's product and category ecosystem, Previous exposure to machine learning concepts, Previous exposure to machine learning algorithms, Demonstrated ability to adapt to evolving technologies in the ML domain, Demonstrated ability to adapt to evolving methodologies in the ML domain

What You'll Do.

Support Machine Learning (ML) models

Perform data annotation

Support data scientists

Develop classification algorithms

Collaborate with cross-functional teams

Ensure data annotation tasks align with project objectives

Ensure data annotation tasks align with project timelines

Maintain high-quality standards for annotated data

Optimize model performance

Continuously evaluate annotation processes

Improve annotation processes

How You'll Work.

Team & Collaboration

Cross-functional teams

Process & Methodology

Multiple simultaneous projects

Full 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 long-term 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 Amazon’s 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 cross-functionally with technical, operations, and business teams to design scalable and automated solutions to customer problems. Amazon is Earth’s most customer-centric 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 cross-functional teams to ensure data annotation tasks align with project objectives and t

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