Catalog Specialist, WWRR Science Annotation Team

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, 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: - 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. null