Data Scientist, Research Intern, PhD, Summer 2025 To apply for this role, you must complete your application on Google Careers directly using this link.
Please note:
Participation in the internship program requires that you are located in the United States for the duration of the internship program.
This role may also be located in our Playa Vista, CA campus.
This internship is intended for students in their penultimate academic year, who are pursuing a PhD degree program in a quantitative discipline (e.g., statistics, biostatistics, physics, applied mathematics, operations research, economics).
Currently pursuing a PhD degree in a quantitative discipline (e.g., statistics, biostatistics, physics, applied mathematics, operations research, economics).
Experience with statistical methods (linear models, multivariate analysis, stochastic processes, sampling methods, etc.).
Experience with data analysis.
Experience using R or Python and technology to work with datasets such as scripting or statistical software (R, SAS, etc.).
Preferred qualifications:
Currently attending a degree program in the US and available to work full time for 12 weeks outside of university term time.
In their penultimate academic year or returning to a degree program after completion of the internship.
Ability to draw conclusions from data and recommend actions.
Ability to take on a leadership role and take initiative.
Interest in teaching others and learning new techniques.
About the job
At Google, data drives all of our decision-making. In the Data Scientist – Research role, you work all across the organization to help shape Google's business and technical strategies by processing, analyzing, and interpreting huge data sets. Using analytical excellence and statistical methods, you mine through data to identify opportunities for Google and our clients to operate more efficiently, from enhancing advertising efficacy to network infrastructure optimization to studying user behavior. You will work with Engineers, Product Managers, Sales Associates, and Marketing teams to adjust Google's practices according to your findings. Identifying the problem is only half the job; you also figure out the solution.
Google is and always will be an engineering company. We hire people with a broad set of technical skills who are ready to address some of technology's greatest challenges and make an impact on millions, if not billions, of users. At Google, engineers not only revolutionize search, they routinely work on massive scalability and storage solutions, large-scale applications, and entirely new platforms for developers around the world. From Google Ads to Chrome, Android to YouTube, Social to Local, Google engineers are changing the world one technological achievement after another.
Compensation
The US base salary range for this full-time position is $103,000-$136,000. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
Work with large complex data sets, solve difficult non-routine analysis problems, and apply advanced analytical methods. Conduct analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
Build and prototype analysis pipelines iteratively to provide insights at scale. Develop a comprehensive understanding of Google data structures and metrics, advocating for changes.
Interact cross-functionally with a wide variety of people and teams. Work closely with engineers to identify opportunities, design and assess improvements to Google products.
Make business recommendations (e.g., cost-benefit, forecasting, experiment analysis) with effective presentations of findings at multiple levels of stakeholders through visual displays of quantitative information.
Research and develop analysis, forecasting, and optimization methods to improve the quality of Google's user products.
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