
Staff Research Data Scientist, Search Ads Metrics
Mountain View, CAJob$207–300K/yrSeen todaySeen in employer's feed today
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Requirements
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Job overview
The Staff Research Data Scientist will guide product development and executive decisions with data for Google’s Search and other ads products. The role measures the long-term impact of product changes, identifies growth opportunities through data analysis, and evaluates tradeoffs among user, advertiser, and Google value. It leads data scientists and collaborates with product, engineering, and executive stakeholders to drive data-informed development and business growth.
Skills & qualifications
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Full job description
Staff Research Data Scientist, Search Ads Metrics
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corporate_fare Google place Mountain View, CA, USA
Advanced
Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in domain.
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XIn most instances, this position requires in-person interviews as part of the hiring process.
Minimum qualifications:
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Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
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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 work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 8 years of work experience with a PhD degree.
About the job
Ads Metrics is the Data Scientist team for Search and O&O 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 Demand Gen Campaigns, Local Ads, Travel Ads, etc. These products are the heart of Google’s business in annual business, are complex, advanced, and they are rapidly growing and evolving.
In this role, you will guide product development and executive decisions with data. You will measure the long term impact of all the changes Google makes on users, advertisers, and Google systems with innovative experiment designs; identify new growth opportunities with deep data analysis; and understand the tradeoffs between user, advertiser and Google value with principled frameworks. You will work closely with the Engineering/PM collaborators to improve the 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 insightful data science.
Google Ads is at the forefront of AI innovation, applying cutting-edge machine learning and Generative AI models like Gemini to power a multi-billion dollar global business.
Our work directly impacts billions of users by protecting users from harm, improving ad quality, and optimizing campaigns for advertiser return-on-investment. We foster a culture of deep collaboration, partnering closely with teams like Google Research and DeepMind to solve complex challenges. Join us to work on state-of-the-art AI, take on problems at an unparalleled scale, and build the next generation of advertising technology.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more aboutbenefits at Google (https://www.google.com/about/careers/applications/benefits/) .
Responsibilities
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Lead a team of data scientists to contribute to ads business growth by initiating, executing, and presenting impactful analysis and modeling projects.
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Optimize the Search Ads serving system by delivering valuable business insights from mathematical models.
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Coach and mentor data scientists by setting clear expectations, evaluating performance, and providing challenges to stretch their skills.
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Collaborate with product, engineering, executive stakeholders, and other organizations to understand needs, assist in decision-making, and align on solutions.
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Navigate multiple stakeholders and organizational complexity to drive data-driven product development.
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .
Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See alsoGoogle's EEO Policy (https://www.google.com/about/careers/applications/eeo/) ,Know your rights: workplace discrimination is illegal (https://careers.google.com/jobs/dist/legal/EEOC\_KnowYourRights\_10\_20.pdf) ,Belonging at Google (https://about.google/belonging/) , andHow we hire (https://careers.google.com/how-we-hire/) .
If you have a need that requires accommodation, please let us know by completing ourAccommodations for Applicants form (https://goo.gl/forms/aBt6Pu71i1kzpLHe2) .
Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.
Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also https://careers.google.com/eeo/ and https://careers.google.com/jobs/dist/legal/OFCCP_EEO_Post.pdf If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form: https://goo.gl/forms/aBt6Pu71i1kzpLHe2.
How this job compares
Set against the 4,636 open Data Scientist jobs on Olive Jobs, counted November 10, 2026.
- Pay
- This posting$207–300K/yr
- California median$155–235K/yr664 salary ranges
- US median$133–210K/yr3,662 salary ranges
This range's midpoint, $254K, is 27% above the California median midpoint ($200K) — in the top quarter of Data Scientist salary ranges in California.
- Openings
- Olive Jobs lists 798 open Data Scientist jobs in California and 4,636 across the US. 7% of them nationwide are listed as remote or flexible.
- Experience
- This posting asks for at least 6 years of experience; Data Scientist postings that state a minimum ask for 5 years at the median (4,024 postings).
- Education
- This posting asks for a master's degree; 554 of the 4,636 open Data Scientist jobs (12%) ask for a master's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 10, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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