Are you passionate about building scalable data pipelines and dashboards that power machine learning innovation? Do you thrive at the intersection of data engineering, AWS cloud architecture, and automation? Join the Worldwide Returns, ReCommerce & Sustainability team where your technical expertise will directly support high-quality training data that fuels ML models—helping Amazon achieve zero waste, zero cost of returns, and zero defects. As a Science Annotation Operations Analyst, you'll own end-to-end data pipelines that extract, validate, and consolidate annotation metrics from AWS and SageMaker. You'll build production dashboards, create custom annotation interfaces, and automate critical workflows—all while collaborating with Program Managers, Science Specialists, and cross-functional teams. This role offers you the opportunity to leverage Python, AWS services, and web development skills to solve real problems that impact both customers and the planet. Responsibilities Design and maintain scalable data pipelines that extract, parse, validate, and consolidate annotation metrics from AWS and SageMaker, ensuring data quality and auditability throughout the lifecycle - Build and operate production dashboards on EC2 covering the full data lifecycle (ingest, validate, score, publish) using technologies like Plotly Dash or Streamlit - Implement secure, least-privilege cross-account AWS integrations using IAM, STS, Lambda, and API Gateway to enable seamless data ingestion from multiple source accounts - Develop custom SageMaker Ground Truth labeling templates using HTML and JavaScript with conditional logic that transform written SOPs into validated annotation interfaces - Automate recurring manual processes including monthly consolidation, historical backfills, and scheduled jobs while maintaining alerting, backups, and deployment workflows to improve operational efficiency A day in the life You'll collaborate with Program Managers, Leads, and Science Annotations Specialists to tackle technical challenges that span the data lifecycle. You could start with debugging a Python script that processes annotation metrics with pandas and boto3, followed by deploying a new dashboard feature to EC2. Later, you could be writing SQL queries to validate data quality, configuring IAM policies for secure cross-account access, or building a new annotation UI template in HTML and JavaScript. You'll use Git for version control and Linux command-line tools to manage deployment workflows, all while serving as the technical POC for your team. About the team The Worldwide Returns, ReCommerce & Sustainability team is dedicated to making zero happen—zero cost of returns, zero waste, and zero defects. We're an agile and inclusive organization that innovates to create long-term value by investing in our people and our planet. Our team spans business, product, operations, data, and software engineering disciplines working together to manage the lifecycle of returned and damaged products. You'll partner across teams to help customers discover great deals on quality used and open box items, improve the returns experience, and reduce waste in reverse logistics. As part of this mission-driven team, you'll be a builder and an owner, collaborating cross-functionally to design scalable solutions. At Amazon, Earth is our customer too—join us and help innovate for a more sustainable future. - Bachelor's degree within last 12 months in computer science, machine learning, engineering, or related fields, or experience with data scripting languages (e.g., SQL, Python, R, or equivalent) or statistical/mathematical software (e.g., R, SAS, Matlab, or equivalent) - Experience with AWS Services including EC2, Lambda, S3, DynamoDB, SQS - Experience building web based dashboards using common frameworks - SageMaker Ground Truth experience - ML / annotation-operations domain familiarity - Experience standardizing metrics and processes across teams 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.
