> Markdown version of [/jobs/ext/2292707-sr-data-scientist-amazon-publisher-cloud](https://www.wearedevelopers.com/jobs/ext/2292707-sr-data-scientist-amazon-publisher-cloud). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Data Scientist, Amazon Publisher Cloud - **Company:** Amazon.com, Inc. - **Location:** New York, NY, United States - **Experience:** Expert - **Salary:** $175,100.0 - $236,900.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Cloud Computing, Data Governance, Data Security, Data Visualization, Query Languages, R (Programming Language), Mobile Application Software, Python (Programming Language), Logistic Regression, MATLAB, Mathematical Software, Power BI, SAS (Software), SQL Databases, Tableau (Software), Scripting, Large Language Models, Data Pipelines - **Published:** August 29, 2026 - **Apply:** https://www.amazon.jobs/en/jobs/10510833/sr-data-scientist-amazon-publisher-cloud ## About the Role The ideal candidate will have deep curiosity and creativity to build data science based solutions. Should demonstrate ability to incorporate latest tech, tools, and methodologies like generate AI and LLMs to enhance our product offerings. Lastly, have experience and comfort working with product, engineering, and Data Science peers within and across teams., 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 - Bachelor's degree - Experience with statistical models e.g. multinomial logistic regression Preferred Qualifications - 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 In this role, you'll develop sophisticated methodologies and models that enable secure data collaboration between publishers and advertisers while maintaining privacy and data governance standards. - Design and implement experimental frameworks to validate Clean Room collaboration methodologies and measure their effectiveness - Develop statistical models and algorithms that power privacy-preserving data analysis capabilities - Lead end-to-end analysis projects to derive actionable insights from cross-party data collaborations - Partner with product teams to translate business requirements into technical solutions - Create reproducible analysis frameworks and documentation A day in the life - Meet with Product Managers to scope requirements for a new cross-publisher audience overlap analysis feature - Write and test code for a new measurement methodology that enables stakeholders to understand campaign effectiveness while preserving user privacy - Design and document statistical approaches for a new clean room collaboration use case - Conduct deep-dive analyses and run experiments to validate new methodologies against industry standards - Present findings and recommendations to leadership and stakeholders - Contribute to the team's technical roadmap and architecture decisions About the team APC Team comprises of smart, skilled, and driven professionals across leadership, product, engineering, data science, business development, and customer success function. We sit within Amazon Publisher Services (APS) business, which helps digital publishers around the world build and grow thriving businesses. We provide services and advanced technologies to web, mobile app and advanced TV publishers of all sizes, including many of comScore's global top 100, to help them monetize their content with demand from multiple programmatic buyers. ## Related Videos - [Beyond Dashboards: Fixing Text-to-SQL with Semantic RAG](https://www.wearedevelopers.com/videos/2036-beyond-dashboards-fixing-text-to-sql-with-semantic-rag) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [JavaScript? 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