Impress employers and recruiters.
Choose from hundreds of resume examples.

Target Resume Now

Tailor your resume to this Senior Data Scientist, Customer Experience and Business Trends role.

Rezi rewrites your resume against Amazon's job description. Free.

Resume score gauge reading 58 out of 100

Don't guess if your resume is good enough.

See how it scores against the Senior Data Scientist, Customer Experience and Business Trends posting at Amazon — free, in seconds.

About the Role

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.

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).

Requirements

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.

Skills

Statistical modeling
Machine learning
Forecasting
Causal inference
Segmentation
Anomaly detection
SQL
Python
R
Data scripting
Metric definition
KPI definition
Communication
Experimentation/A-B testing
Modern ML tooling
Cloud data environments (AWS, Spark)
Mentoring scientists/analysts
Technical leadership
Retail analytics
E-commerce analytics
CPG analytics
Competitive analytics
Market-share analytics
Share-of-wallet
Category penetration
Price benchmarking
Selection benchmarking
Fulfillment benchmarking

Location

USA, VA, Arlington
USA, WA, Seattle

Work Type

Full-time

Experience Level

Senior

Education Level

Master's degree or above in a quantitative field
PhD

Salary/Compensations

159,200.00 - 215,300.00 USD annually

Benefits

Sign-on payments
Restricted stock units (RSUs)
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
Parental leave

About the Company

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.

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.
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 [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.