Drive Amazon's defect elimination through AI-powered detection pipelines that scale coverage across millions of product returns, translating data into upstream interventions that prevent defects before they reach customers.

Lead a team of Business Analysts and Business Intelligence Engineers to prototype ML models identifying defect patterns across product catalog, customer returns, and seller feedback—building analytical frameworks that reduce investigation time and deliver measurable cost savings.



Key job responsibilities


Defect Detection & Root Cause Pipeline

Establish roadmap for scaling defect detection coverage and set KPIs for accuracy
Prototype ML/AI models to identify new defect patterns across product families
Build analytical frameworks that reduce investigation time and ensure auditability
Create self-service dashboards with data quality standards for detection accuracy

Team Development & Technical Leadership

Hire and develop specialists in pattern recognition and root cause analysis
Create technical growth paths from exploratory analysis to AI-powered classification
Establish best practices for analyzing large-scale returns data
Collaborate with engineering, data, and product teams to prioritize investigations and validate findings

Business Impact & Stakeholder Engagement

Present data-driven defect identification approaches in business reviews showing multi-million dollar cost saving opportunities
Influence senior leadership on prioritizing high-impact defect categories

Product Launch Support

Define requirements for defect identification tools from a returns reduction perspective
Create business requirement documents with success metrics and governance frameworks
Track and validate product performance metrics, document ROI, and monitor feature adoption

About the team
Our mission is to eliminate defects that cause customer returns, improving the shopping experience while reducing costs across Amazon's fulfillment network. We combine deep-dive analysis with innovative solutions to identify and prevent product issues before they reach customers.

We believe every return represents an opportunity to learn and improve. By understanding root causes and building scalable detection systems, we transform reactive problem-solving into proactive defect prevention—creating lasting value for customers and the business.