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Data Scientist Google Jobs (NOW HIRING)

D. in Computer Science, Statistics, Mathematics, Data Science, Economics, Physics, Operations ... Learn more about benefits at Google. Position reports to the Google San Bruno, CA office & may ...

Data Scientist

San Bruno, CA · On-site

$164.45 - $211/hr

corporate_fare Google place San Bruno, CA, USA Mid Experience driving progress, solving problems ... D. in Computer Science, Statistics, Mathematics, Data Science, Economics, Physics, Operations ...

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Data Scientist Google information

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$37.5K

$122.7K

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How much do data scientist google jobs pay per year?

As of Aug 28, 2026, the average yearly pay for data scientist google in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What does a data scientist at Google do?

A Data Scientist at Google is responsible for analyzing large and complex data sets to help inform business decisions, develop new products, and improve user experiences. They use statistical analysis, machine learning, and data visualization techniques to uncover insights from data. Data Scientists at Google often collaborate with engineers, product managers, and other stakeholders to solve challenging problems and drive innovation across various products and services.

What are the key skills and qualifications needed to thrive as a data scientist at Google?

To thrive as a Data Scientist at Google, you need strong expertise in statistics, machine learning, data analysis, and a relevant degree such as computer science or mathematics. Familiarity with programming languages like Python or R, experience with big data tools (e.g., TensorFlow, SQL, Hadoop), and possibly certifications in data science platforms are typically required. Excellent problem-solving, communication, and collaboration skills help you translate data insights into impactful business solutions. These skills ensure you can extract meaningful insights from complex data and drive innovation in a fast-paced, data-driven environment.

How does a data scientist at Google typically collaborate with cross-functional teams to deliver impactful projects?

At Google, Data Scientists frequently work alongside engineers, product managers, UX researchers, and business analysts to translate complex data insights into actionable product improvements. Collaboration often involves regular meetings to align on project goals, brainstorming sessions to identify potential data-driven solutions, and iterative feedback cycles to refine models or analyses. Open communication and a collaborative mindset are key, as Data Scientists are expected to clearly articulate findings to both technical and non-technical stakeholders, ensuring their work drives meaningful business outcomes.

What is the difference between Data Scientist Google vs Data Analyst Google?

AspectData Scientist GoogleData Analyst Google
Required CredentialsBachelor's/Master's in CS, Statistics, or related; often a PhD for advanced rolesBachelor's in related fields; certifications like Google Data Analytics are common
Work EnvironmentDeveloping models, advanced analytics, machine learning projectsData cleaning, reporting, visualization, basic analysis
Employer & Industry UsageTech giants, startups, industries leveraging AI and MLBusiness intelligence, marketing, finance across various sectors

Data Scientist Google focuses on building predictive models and advanced analytics, requiring higher technical skills and often advanced degrees. Data Analyst Google handles data interpretation, reporting, and visualization, with a focus on business insights. Both roles are essential but differ in complexity and scope.

Can a Data Scientist get a job in Google?

Yes, Data Scientists can get jobs at Google, which regularly hires for data science roles requiring strong skills in statistics, machine learning, programming (Python, R), and data analysis. Candidates typically need relevant experience, a strong educational background, and proficiency with tools like TensorFlow or BigQuery. Google's hiring process is competitive and often involves technical interviews and project assessments.
More about Data Scientist Google jobs

What cities are hiring for Data Scientist Google jobs?

Cities with the most Data Scientist Google job openings:

What states have the most Data Scientist Google jobs?

States with the most job openings for Data Scientist Google jobs include:

Infographic showing various Data Scientist Google job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Business Data Scientist, Google Analytics

Mountain View, CA • On-site


Google Inc.
Software Development • 10K+ employees

8.8

Company rating: 8.8 out of 10

Based on 103 frontline employees who took The Breakroom Quiz

48th of 246 rated software companies

Free food

Great coworkers

People enjoy working here


$138 - $197/hr

Other

This job post has expired 4 days ago. Applications are no longer accepted.


Job description

Business Data Scientist, Google Analytics

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corporate_fare Google place Mountain View, CA, USA ; New York, NY, USA

Mid

Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area.

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X Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; New York, NY, USA.

  • Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
  • 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
Preferred qualifications:
  • 4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
About the job

Google's leadership team hand-picks thorny business challenges, and members of BizOps work in small teams to find solutions. As part of this team you fully immerse yourself in data collection, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior-level executives, roll-up your sleeves to help drive implementation and check back-in to see the impact of your recommendations.

The Ads and Commerce Finance team provides strategic analysis and forecasting of core business-generating products to executive audiences. As part of this team, you will have a unique perspective on key digital advertising businesses, services, and the ecosystems within which they operate. You will serve as a strategic partner to business leaders across Product and Engineering to drive impact through a grounding in hard data, an independent point of view, a bias to action, and a collaborative approach.

In this role, you will serve as a data scientist supporting the media effectiveness measurement team, which aims to help advertisers measure the effectiveness of their digital ad spend leveraging a full-funnel set of metrics. You will be at the center of driving analytics, insights, and measurement impact across primary web analytics and campaign management platforms. You will lead the holistic finance strategy for these product suites, oversee advanced analytics, refine pricing rate cards, and partner with Product Management, Engineering, Product Strategy, Go-To-Market, and cross-functional Finance teams to guide executive decisions.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $138000 - $197000 (USD) + 15% bonus target + equity + benefits Learn more about benefits at Google .

About the job

Google's leadership team hand-picks thorny business challenges, and members of BizOps work in small teams to find solutions. As part of this team you fully immerse yourself in data collection, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior-level executives, roll-up your sleeves to help drive implementation and check back-in to see the impact of your recommendations.

The Ads and Commerce Finance team provides strategic analysis and forecasting of core business-generating products to executive audiences. As part of this team, you will have a unique perspective on key digital advertising businesses, services, and the ecosystems within which they operate. You will serve as a strategic partner to business leaders across Product and Engineering to drive impact through a grounding in hard data, an independent point of view, a bias to action, and a collaborative approach.

In this role, you will serve as a data scientist supporting the media effectiveness measurement team, which aims to help advertisers measure the effectiveness of their digital ad spend leveraging a full-funnel set of metrics. You will be at the center of driving analytics, insights, and measurement impact across primary web analytics and campaign management platforms. You will lead the holistic finance strategy for these product suites, oversee advanced analytics, refine pricing rate cards, and partner with Product Management, Engineering, Product Strategy, Go-To-Market, and cross-functional Finance teams to guide executive decisions.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $138000 - $197000 (USD) + 15% bonus target + equity + benefits Learn more about benefits at Google .

  • Shape and scrutinize the commercial strategy for the GA and CM product suites, evaluating the impact on business and the broader Google Ads ecosystem.
  • Drive the annual business plan and establish operational targets, providing executive-level business performance updates and actionable insights.
  • Architect sophisticated market sizing and opportunity models to project medium-to-long-term product adoption and growth trajectories.
  • Drive cross-functional thinking to assess the incrementality and strategic benefits of the product suites within the larger Google user ecosystem.
  • Act as a strategic thought partner on incentive fund investments, ensuring rigorous disbursement operations and flagging risks to fund deployment.

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 also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .

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.

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 and 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.

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