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# Data Scientist , Prime Video - Advertising

- **Company:** Amazon.com, Inc.
- **Location:** Arlington, VA, United States
- **Experience:** Experienced
- **Salary:** $159,200.0 - $236,900.0
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Amazon Web Services, Data Visualization, Query Languages, R (Programming Language), Python (Programming Language), Logistic Regression, Mathematical Software, Power BI, SAS (Software), Software Deployment, SQL Databases, Tableau (Software), Scripting, Data Analytics, Data Pipelines
- **Published:** May 16, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=e22116dcfe2f783b

## About the Role

* 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
 * Experience with statistical methods (e.g., A/B Testing, Regression), * 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

## Description

* 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


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