Senior Data Scientist, Customer Experience and Business Trends

16 set - Asti
Amazon

Senior Data Scientist, Customer Experience and Business Trends
Job ID: 10536465 | Amazon.com Services LLC
Amazon's Customer Experience and Business Trends (CXBT) organization is hiring a Senior Data Scientist for its Benchmarking, Economics, Analytics and Measurement (BEAM) team. BEAM's mission is to improve customer experience across every Amazon business by turning fragmented internal and external data into decision-grade intelligence for senior leaders.
This role anchors our Topline View of Retail initiative: an always-on competitive intelligence capability that fuses third-party transaction panels with Amazon's internal signals to answer how Amazon is winning or losing share of wallet, across segments, categories, and time. You will not just analyze metrics — you will decide which metrics should exist, then build the statistical and machine learning models that generate, forecast, and explain them. Given a new business question and a pile of raw panel and internal data, you are the person who defines what "competitiveness" means, translates it into a defensible,



reproducible metric and model, and defends the methodology to skeptical senior stakeholders.
We are looking for someone with exceptional business judgment and metric intuition, paired with deep hands-on modeling skills: a strong point of view on what to measure, and the technical ability to build the models that measure it at scale. You should be equally comfortable pressure-testing a model's assumptions and explaining its "so what" to a VP in two sentences.
Key job responsibilities
- Own the definition, methodology, and evolution of BEAM's competitiveness metrics (e.g., share-of-wallet, segment-level penetration, price/selection/fulfillment competitiveness), including the trade-offs behind each definition.
- Design, build, and validate statistical and machine learning models — forecasting, causal inference, segmentation, and anomaly detection — that power those metrics and surface competitive shifts.
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