> Markdown version of [/jobs/ext/3461303-senior-product-data-scientist-education](https://www.wearedevelopers.com/jobs/ext/3461303-senior-product-data-scientist-education). 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). --- # Senior Product Data Scientist, Education - **Company:** Google LLC - **Location:** New York, NY, United States - **Experience:** Expert - **Salary:** $163,000.0 - $236,000.0 - **Contract:** Permanent contract - **Skills:** Data Analysis, R (Programming Language), Python (Programming Language), SQL Databases, Data Pipelines - **Published:** September 21, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=00d22f7e1679cc21 ## About the Role * Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. * 8 years of work experience using analytics to solve product or business issues, performing statistical analysis, and coding (e.g., Python, R, SQL) (or 5 years work experience with a Master's degree)., * Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. * 8 years of work experience using analytics to solve product or business issues, performing statistical analysis, and coding (e.g., Python, R, SQL). ## Description * Build and manage relationships with investigative, engineering, and product leaders in partner product areas (PAs) to align on metric instrumentation, resolve data dependencies, and co-develop analyses that influence shared product roadmaps and resource allocation. * Define, own and evolve product/business success metrics. Report, analyze and forecast trends of key product/business metrics and make recommendations to improve them. Lead the design, analysis, and interpretation of product experiments. * Apply technical expertise with observational data analysis, modeling, and causal inference to answer the product/business questions. * Architect unified data pipelines and single-source-of-truth measurement frameworks by integrating cross-PA data sources to map end-to-end user journeys and evaluate cross-product performance. * Deliver effective presentations of data-driven insights and recommendations to multiple levels of stakeholders.