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 cutting-edge 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.

Need candidates in language proficiency in: Spanish

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 timelines
- Maintain high-quality 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 deep-dive on complex problems
- Ability to manage multiple simultaneous projects requiring frequent communication, organization/time management and problem-solving skills

BASIC QUALIFICATIONS

- • 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
- • 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

PREFERRED QUALIFICATIONS

- Bachelor's degree or above in computer science, computer engineering, or related field, or experience in communicating technically, at a level appropriate for the audience
- Proven experience in data annotation and labeling for ML model training and evaluation
- Demonstrated ability to adapt to evolving technologies and methodologies in the ML domain

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.

📌 Catalog Specialist, WWRR Science Annotation Team (Hyderabad)
🏢 Amazon.com
📍 Hyderabad