Senior Data Scientist, Customer Experience and Business Trends

Amazon.com Services LLC; Seattle (WA); On-site; USD 150,000 - 210,000; Full time

Job summary

Amazon.com Services LLC's CXBT BEAM team seeks a Senior Data Scientist to lead metric design, model building, and forecasting that explain competitiveness across segments and time. You will fuse third-party panels with internal signals, build scalable pipelines, and defend methodologies to senior leaders.

You will translate business questions into measurable metrics, validate models, and produce recurring reports for CXBT and business-line leadership.

Qualifications

• Master's degree or higher in a quantitative field or PhD with 6+ years of experience in data science.
• Experience applying statistical modeling and ML methods to business problems.
• Proficiency with SQL and Python or R and building analyses on large, messy datasets.
• Demonstrated experience defining metrics and KPIs from scratch and connecting them to business decisions.
• Experience communicating analytical and modeling results to senior, non-technical audiences in writing.

Responsibilities

• Own the definition, methodology, and evolution of BEAM's competitiveness metrics (e.g., share-of-wallet, segment-level penetration, price/selection/fulfillment competitiveness).
• Design, build, and validate statistical and ML models—forecasting, causal inference, segmentation, anomaly detection.
• Integrate third-party panel data with internal signals into reproducible modeling pipelines trusted by leadership.
• Translate ambiguous business questions into the right metric, model, data cut, and defensible answer.
• Productionize models and analyses to run as recurring reporting mechanisms with data engineers.
• Produce monthly flash reports and deep-dive narratives turning models into decisions for leadership.
• Set analytical rigor standards, including methodology reviews, documentation, and guardrails.
• Mentor and uplift other scientists and BIEs on modeling and metric-design decisions.

Skills

Statistical modeling

Machine learning

Metrics definition

Communicating results

Education

Master's degree or PhD in a quantitative field

Tools

SQL

Python

R

AWS

Spark

Job description

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.
• Pull together disparate third-party transaction-panel data and internal Amazon signals into coherent, reproducible modeling pipelines that leadership can trust for recurring reporting.
• Translate ambiguous business questions ("are we losing ground in grocery?") into the right metric, the right model, the right cut of data, and a clear, defensible answer.
• Productionize models and analyses so they run reliably as recurring mechanisms, partnering with data engineers to scale and automate.
• Produce monthly flash reports and deep-dive narratives that turn models and metrics into decisions for CXBT and business-line leadership.
• Set the standard for analytical and modeling rigor on the team - methodology reviews, documentation, and guardrails against misleading cuts.
• Mentor and technically uplift other scientists and BIEs on the team - reviewing modeling approaches and raising the bar on rigor (e.g., partnering with our Data Scientist on the MatchIQ model to strengthen methodology and validation).

About the team

CXBT is a group of diverse functions dedicated to understanding, improving, and influencing customer experience globally, across all of Amazon. We are builders who develop products, services, and data-driven approaches that shape offerings for nearly every Amazon business and customer type - consumers, developers, sellers, brands, employees, investors, streamers, and gamers. We work backwards from customer needs, combine technical and non-technical methods, and track industry and business trends. Our roles span Product Managers, Data Scientists, Economists, Business Intelligence Engineers, Data Engine, Applied Scentist, and Product Manager.

Basic Qualifications

• Master's degree or above in a quantitative field, or PhD and 6+ years of data scientist experience
• Experience applying statistical modeling and machine learning methods (e.g., regression, forecasting/time series, classification, clustering, causal inference) to business problems.
• Proficiency with data scripting and modeling languages (SQL and Python or R) and building analyses on large, messy datasets.
• Demonstrated experience defining metrics and KPIs from scratch and connecting them to business decisions.
• Experience communicating analytical and modeling results to senior, non-technical business audiences in writing.

Preferred Qualifications

• Familiarity with experimentation/A-B testing and with modern ML tooling and cloud data environments (e.g., AWS, Spark).
• Experience mentoring scientists/analysts and providing technical leadership on modeling and metric-design decisions.
• Strong background in retail, e-commerce, or CPG competitive and market-share analytics (share-of-wallet, category penetration, price/selection benchmarking).

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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 applica