ML Annotations & Calibration Specialist II, WW RCX - Product Lifecycle Support
Amazon's Product Lifecycle Support (PLS) offers relevant post-purchase product support to customers, and empowers them to make the most of the products purchased on Amazon. By solving post-purchase product issues, we prevent avoidable returns and help the planet by extending the life of products, thereby generating positive financial and environmental impacts.
PLS first launched in Q4 2015 featuring a warranty repair option for Samsung laptops surfaced during the returns process in the Online Return Center (ORC). Since then, PLS has grown substantially, and now offers customers eight product support options:
- Live call & chat with Amazon product support agent available up to 6 months,
- Live call & chat with the brand product support agent available up to 2 years,
- Contact the manufacturer yourself by accessing brand phone number and/or support website available up to 2 years,
- Access free warranty repair services available up to 2 years,
- Access free replacement parts available until return window,
- Access other sustainable end-of-life options such as trade-in, resell, refill, recycle, donate, etc. available up to 2 years,
- Help yourself by watching step-by-step video instructions provided by the brand,
- Help yourself by following step-by-step instructions provided by the brand.
The Product Lifecycle Support (PLS) team at Amazon is looking for a Catalog Specialist II to support Annotations and Machine Learning (ML) calibrations. This role requires strong analytical skills to derive insights from Amazon's catalog and corresponding return reasons, contributing to product support optimization and customer experience improvements.
Key Job Responsibilities
- Lead and oversee annotations and ML calibration audits, ensuring accuracy and adherence to SOPs.
- Analyze Amazon catalog data and return trends to identify patterns and opportunities to reduce avoidable returns.
- Develop and refine scalable SOPs for new and ambiguous processes.
- Use deep dive skills to troubleshoot and resolve catalog discrepancies that impact post-purchase support.
- Communicate findings and insights effectively with cross-functional stakeholders to drive improvements in product lifecycle support.
- Work closely with ML teams to fine-tune system-generated outputs by curating and optimizing prompts/instructions.
- Validate catalog data using approved sources and improve system precision through feedback loops.
- Utilize SQL, VBA, and Advanced Excel to analyze large datasets and make data-driven recommendations.
- Monitor and enhance catalog accuracy, product support content, and customer experience.
- Collaborate on process automation and continuous improvement initiatives to enhance PLS efficiency.
- Ensure availability during the first half of PST working hours to actively engage in business forums, contribute to key discussions, and influence critical decision-making.
BASIC QUALIFICATIONS
- 2+ years of program or project management experience
- Knowledge of SQL and Advanced Excel (Array and Statistical formulas)
- Experience using data to influence business decisions
PREFERRED QUALIFICATIONS
- Knowledge of visualization tools such as Tableau, Datazen, SSRS
- Understanding of machine learning processes and annotation workflows.
- Experience in content management, quality audits, or e-commerce operations.
- Familiarity with Amazon's product catalog, return reasons, and seller operations.
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 this link for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.