Business Analyst, North America Surface Transportation Customer Experience (NAST CX)
Summary
Business Analyst on Amazon's surface transportation customer experience team—designs analytical frameworks, builds SQL/ETL pipelines, and leverages generative AI (Bedrock, Q, LLMs) to surface delivery-defect insights, build predictive models, and automate reporting.
Amazon's North America Surface Transportation Customer Experience team is seeking a Business Analyst to support data-driven decision making that improves the delivery experience for millions of customers. In this role, you will be responsible for designing, building, and maintaining analytical frameworks, products, and deep-dive analyses that illuminate customer experience trends, identify root causes of defects, and quantify the impact of product and operational initiatives across our surface transportation network.
You will serve as a key analytical partner to Product Managers, Program Managers, and Operations leaders — translating complex transportation and customer data into clear, actionable insights. The ideal candidate is passionate about using data to tell stories, thrives in ambiguity, and is energized by working at the intersection of customer experience and large-scale logistics.
Key job responsibilities
- AI-Assisted Analysis: Leverage generative AI tools and large language models (e.g., Amazon Bedrock, Amazon Q) to accelerate data exploration, pattern recognition, and insight generation across large, complex data sets
- Predictive Analytics: Partner with science teams to develop and validate predictive models that forecast customer experience outcomes such as delivery delays, contact rate spikes, and defect trends across the surface transportation network
- Automated Insight Generation: Build and refine AI-assisted workflows that automate recurring analyses, anomaly detection, and narrative summarization to reduce manual effort and accelerate time-to-insight
- AI Tool Evaluation & Adoption: Stay current on emerging AI/ML tools and capabilities; evaluate and champion new AI-powered analytics solutions that can enhance the team's analytical capabilities and decision-making speed
- Data Pipelines: Write and optimize SQL queries across large-scale data sets; build ETL pipelines to automate recurring data workflows
- Scalable Solutions: Identify opportunities to automate manual reporting and analysis processes using AI and scripting tools, improving team efficiency and data reliability
- Cross-Functional Collaboration: Partner closely with Product Managers, Program Managers, Science, Engineering, and Operations teams to provide analytical support for strategic initiatives
You will serve as a key analytical partner to Product Managers, Program Managers, and Operations leaders — translating complex transportation and customer data into clear, actionable insights. The ideal candidate is passionate about using data to tell stories, thrives in ambiguity, and is energized by working at the intersection of customer experience and large-scale logistics.
Key job responsibilities
- AI-Assisted Analysis: Leverage generative AI tools and large language models (e.g., Amazon Bedrock, Amazon Q) to accelerate data exploration, pattern recognition, and insight generation across large, complex data sets
- Predictive Analytics: Partner with science teams to develop and validate predictive models that forecast customer experience outcomes such as delivery delays, contact rate spikes, and defect trends across the surface transportation network
- Automated Insight Generation: Build and refine AI-assisted workflows that automate recurring analyses, anomaly detection, and narrative summarization to reduce manual effort and accelerate time-to-insight
- AI Tool Evaluation & Adoption: Stay current on emerging AI/ML tools and capabilities; evaluate and champion new AI-powered analytics solutions that can enhance the team's analytical capabilities and decision-making speed
- Data Pipelines: Write and optimize SQL queries across large-scale data sets; build ETL pipelines to automate recurring data workflows
- Scalable Solutions: Identify opportunities to automate manual reporting and analysis processes using AI and scripting tools, improving team efficiency and data reliability
- Cross-Functional Collaboration: Partner closely with Product Managers, Program Managers, Science, Engineering, and Operations teams to provide analytical support for strategic initiatives