Senior Data Scientist, Customer Experience and Business Trends

Amazon Science; Seattle (WA); On-site; USD 159,000 - 215,000; Full time

Job summary

Amazon Science's BEAM team seeks a Senior Data Scientist to lead the design and production of competitive metrics and machine learning models. You will fuse third‑party data with internal signals to quantify share of wallet and market competitiveness across segments and time.

You will translate complex business questions into defensible metrics, defend methodologies to senior stakeholders, and mentor others while delivering repeatable analyses and reports for CXBT and leadership.

Qualifications

• Master's degree or PhD with 6+ years of data science experience.
• Experience applying statistical modeling and ML methods to business problems.
• Proficiency with SQL and Python or R for large datasets.
• Experience defining metrics and KPIs from scratch and linking them to business decisions.
• Experience communicating analytical and modeling results to senior, non-technical audiences.

Responsibilities

• Define and evolve BEAM competitiveness metrics and definitions.
• Design, build, and validate forecasting, causal inference, segmentation models.
• Integrate third-party panels with internal signals into reproducible pipelines.
• Translate business questions into the right metrics and defensible analyses.
• Productionize models and automate recurring reporting.
• Produce monthly flash reports and deep-dive narratives for leadership.
• Uphold modeling rigor and guardrails against misleading cuts.
• Mentor scientists and uplift team quality.

Skills

Statistical modeling

Machine learning

SQL

Python

R

Data storytelling

Stakeholder communication

Education

Master's degree or PhD in quantitative field

Tools

AWS

Spark

Pandas

Scikit-learn

Job description

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).

Equal Opportunity

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

Accommodations

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 application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Benefits

Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

Salary

USA, VA, Arlington - 159,200.00 - 215,300.00 USD annually

USA, WA, Seattle - 159,200.00 - 215,300.00 USD annually