Long applicationsign-up on Google
Research Data Scientist, Core Metrics
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Salary
≈ $139k – $264k per year (Estimated)
Location
In office (Mountain View)
Seniority
Senior · 5+ years exp
Confirmed on the employer's own hiring board on Oct 24, 2026. First seen by Alion on Oct 23, 2026. Google scores B on the Alion truth index.
Overview
Company
Impact
Profile match
Google is an American technology company founded in 1998 by Larry Page and Sergey Brin and now the principal subsidiary of Alphabet, headquartered in Mountain View, California. It operates the world's dominant search engine and the advertising system built around it, along with YouTube, Android, Chrome, Gmail, Maps, Workspace and Google Cloud, reaching billions of users across nearly every internet-connected market. The company designs its own silicon in the Tensor Processing Unit line, develops the Gemini foundation models through Google DeepMind, and derives most of its revenue from advertising while cloud has become its fastest growing segment.
About the job
Ads Metrics is the Data Science team for Search ads. We support the SAGE (Search Ads and Google Experience) organization in developing the most important ad products at Google - from classic text ads, to rich shopping ads, to exciting new products like Discovery ads. These products - the heart of Google’s business driving $B+ in annual revenue - are complex, advanced, and they are rapidly growing and evolving.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models.
- Use custom data infrastructure or existing data models as appropriate, using specialized knowledge. Design and evaluate models to mathematically express and solve defined problems with limited precedent.
- Gather information, business goals, priorities, and organizational context around the questions to answer, as well as the existing and upcoming data infrastructure.
- Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Independently format, re-structure, and/or validate data to ensure quality, and review the dataset to ensure it is ready for analysis.
Qualifications
Minimum qualifications:
- Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
- 3 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.
Preferred qualifications:
- 5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.
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