Amazon’s Customer eXperience Impressions (CXI) team is hiring a Business Intelligence Engineer (BIE) to build the analytical systems that measure, detect, and explain shifts in customer behavior. This role will focus on developing data products and metrics that quantify how defects (availability, placement, and delivery speed, etc) impact customer decisions, and design scalable data products that surface these insights in real time, and ensure Amazon's most senior leaders have a precise understanding of how customer friction translates into lost demand.

CXI operates at the intersection of customer experience and supply chain optimization. As part of Supply Chain Optimization Technology (SCOT), the team’s data infrastructure captures signals from every stage of the shopping journey—search, detail page, and repeat purchase interactions—to measure when and why customers hesitate, abandon their carts, etc. The BIE will transform these signals into structured analytics, to enable Amazon to diagnose customer experience defects with high precision and determine where intervention is necessary.

Unlike traditional retail, where demand signals rely on completed purchases, we capture the full spectrum of customer intent, including unconverted shopping impressions. These impressions act as a leading indicator of demand, revealing friction points before they manifest as revenue declines or infrequent visits. The BIE will build the measurement mechanism that connect these early signals to downstream business impact, to ensure that Amazon not only detects defects but understands when and how to act on them.


Key job responsibilities
As a BIE on the CXI team, you will need to understand what information is valuable to your internal customers, and work with product, engineering, and science teams to design products that are necessary to extract business insights. You will be responsible for developing the analytical systems that detect when defects in the Amazon shopping experience require intervention, measure the cost of inaction, and assess the precision and recall of intervention strategies. This BIE will support senior leadership reporting on shifts in customer behavior, to enable Amazon to quantify the downstream effects of friction caused by controllable defects.

CXI captures high-dimensional signals from billions of shopping interactions, tracking how customer intent evolves in response to defects. The BIE will develop the analytical pipelines that surface these patterns, to ensure real-time defect detection achieves high recall while minimizing false positives that lead to unnecessary interventions. They will define decision thresholds for action, integrating statistical confidence measures that distinguish between recoverable demand loss and shifts that persist regardless of intervention.

This role requires direct collaboration with applied scientists, engineers, and product teams to establish scalable evaluation frameworks. The BIE will support the development of ML models to quantify the marginal impact of intervention timing, calibrating precision-recall trade-offs in defect correction strategies. They will assess the causal relationship between detected defects and observed customer behavior, to ensure that interventions target high-impact opportunities while avoiding noise.

Beyond intervention mechanics, the BIE will design SVP-level reporting that quantifies systemic shifts in customer engagement. They will track real-time changes in visit-to-purchase rates, model the elasticity of customer response to defect resolution, and generate predictive insights that allow Amazon to anticipate conversion risks before they manifest at scale.

The BIE’s work will provide the foundation for CXI’s next phase of customer experience optimization. By formalizing the measurement of intervention effectiveness, they will define the thresholds at which automated actions outperform passive correction.

This is a highly visible role and will require regular interaction and communication with senior leaders. You must have experience and capability to document your work for technical as well as non-technical audiences. Excellent written and verbal communication skills is a requirement.