Staff Research Data Scientist, Search Ads GenAI
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Staff Research Data Scientist, Search Ads GenAI
207,000–301,000 / Year
Location
Mountain View, CA, USA
Experience
Senior
Posted
Jul 18, 2026
Apply by
August 17, 2026
Applicants
0
Early applicantEasy applyFull-timeWork from Office
Job Description
Minimum qualifications: Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, a related quantitative field, or equivalent practical experience. 8 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of experience with a PhD degree. Preferred qualifications: 10 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 8 years of experience with a PhD degree.
About the job Ads Metrics is the Data Science team for Search and owned and operated ads. You will support the Search Ads and Google Experience (SAGE) organization in developing ad products at Google—from classic text ads and rich shopping ads to new products like demand generation campaigns, local ads, travel ads, and more. These products, driving over $200 billion in annual business, are rapidly growing and evolving. You will guide product development and executive decisions with data. Particularly, you will measure the long-term impact of all the changes you make on users, advertisers, and Google systems with experiment designs, identify new growth opportunities with data analysis, and understand the tradeoffs between user, advertiser, and Google value with principled frameworks. You will work with engineering and product management partners to improve products, and with SAGE executives to understand the growth levers and their impact on business. Your role is to drive long-term value for Google's business with excellent data science. Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We’re made up of multiple teams, building Google’s Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $207000 - $301000 (USD) + 20% bonus target + equity + benefits Learn more about benefits at Google.
Responsibilities Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Format, re-structure, or validate data to ensure quality, and review the dataset to ensure it is ready for analysis. Partner as a Staff Data Scientist on the Ads Metrics team to explore Generative Artificial Intelligence (GenAI) projects on the Artificial Intelligence (AI) mode surface. Evaluate experiments to identify what works versus what does not work, assess how to best serve embedded ads, understand users’ commercial journey on the surface, and develop a strategy for business generation. Communicate with Ads product, engineering, and executive partners, and other organizations (e.g., customer solutions, business) to understand their needs, assist in decision-making, and align on solutions.
Key Responsibilities
- Gather, extract, and compile data across sources using tools like SQL, R, and Python.
- Format, restructure, or validate data to ensure quality and readiness for analysis.
- Partner on Generative Artificial Intelligence (GenAI) projects on the AI mode surface.
- Evaluate experiments to identify effective strategies for serving embedded ads.
- Assess user commercial journeys and develop strategies for business generation.
- Communicate with product, engineering, and executive partners to align on solutions and decision-making.
Requirements
- Master's degree in Statistics
- Data Science
- Mathematics
- Physics
- Economics
- Operations Research
- Engineering
- or a related quantitative field
- PhD degree
Skills Required
PythonRSQLData AnalysisStatistical AnalysisDatabase QueryingCommunicationCollaborationProblem Solving
Benefits
- 20% bonus target
- Equity
- Benefits
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