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Sr Data Scientist, Seller Partner Trust Analytics

Seattle, Washington, United States💼 Full-time🗓 2026-07-07 → 2026-07-09

Core

Develop new ways to build trust and loyalty with sellers by analyzing large-scale streaming, ad delivery, and auction data sets to identify key areas of focus and improve customer experience.

Role type

Sr Data Scientist, Seller Partner Trust Analytics

Builds

Statistical models supporting Supply tier classification, Supply Quality Index, ad tolerance/fatigue scoring, propensity/disengagement prediction, and curated datasets for PVa product, ops, sales, and science.

Domain

E-commerce / Ad-tech / Seller Platform

Deliverable

production ML models | dashboards & analysis

Required skills

SQL, Python, R, SAS, Matlab, statistical modeling (multinomial logistic regression), data querying, data cleaning, A/B testing design, power calculations, holdout structures, north star metric definition, stakeholder partnership

Preferred skills

Data visualization (AWS QuickSight, Tableau, R Shiny), data pipeline management, team leadership and mentorship

Technologies

SQL, Python, R, SAS, Matlab, AWS QuickSight, Tableau, R Shiny

Responsibilities

Design and implement end-to-end data science workflows from data acquisition through production deployment; Build, validate, and maintain statistical models for supply and ad metrics; Partner with product and economist teams to design holdout experiments; Support scalable, self-service analytics by building curated datasets; Identify strategic, data-driven opportunities to improve customer experience and advertiser results; Communicate findings and recommendations to technical and non-technical stakeholders

Seniority

Senior, hands-on IC with strategic vision setting

Rewrite
## Responsibilities - Use advanced statistical and machine learning techniques to extract insights from large-scale streaming, ad delivery, and auction data sets. - Design and implement end-to-end data science workflows from data acquisition and cleaning through model development, offline evaluation, A/B testing, and production deployment in partnership with product and engineering teams - Build, validate, and maintain the statistical models that support the roadmap including Supply tier classification and Supply Quality Index, ad tolerance and fatigue scoring, and propensity and disengagement prediction - Partner with product and economist teams to design hold out experiments to measure impact of Ad load on revenue and customer engagement; define north star metrics, power calculations, holdout structures, and promotion gates for every major lever. - Support scalable, self-service analytics by building curated datasets for PVa product, ops, sales, and science covering supply, yield, CX, and advertiser diversification outcomes. - Partner with product stakeholders and science peers to identify strategic, data-driven opportunities to improve the customer experience and advertiser results. - Communicate findings, conclusions, and recommendations to technical and non-technical stakeholders - Stay up-to-date on the latest data science tools, techniques, and best practices and help evangelize them across the organization ## Requirements - 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience - 4+ years of data scientist experience - Experience with statistical models e.g. multinomial logistic regression ## Nice to Have - 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience - Experience managing data pipelines - Experience as a leader and mentor on a data science team ## Benefits 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 for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
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