Business Data Scientist Intern, PhD, Summer 2026

Business Data Scientist Intern, PhD, Summer 2026

Please complete your application before October 31st, 2025.

Applications will be reviewed on a rolling basis and it's in a candidate's best interest to apply early.

Timing on when you can hear back will vary and can take upwards of 90+ days. If you haven't heard from us in three months about your application, we likely proceeded with other candidates for the role.

Participation in the internship program requires that you are located in the United States for the duration of the internship program.

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).

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for this internship program. To start the application process, you will need an updated CV or resume and a current unofficial or official transcript in English. Click on the "Apply" button on this page and provide the required materials in the appropriate sections (PDFs preferred):

1. In the "Resume Section:" attach an updated CV or resume.
2. In the "Education Section:" attach a current or recent unofficial or official transcript in English.

Applicants in the County of Los Angeles: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.

Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.

This role may also be located in our Playa Vista, CA campus.

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; Ann Arbor, MI, USA; Atlanta, GA, USA; Austin, TX, USA; Boulder, CO, USA; Bellevue, WA, USA; Cambridge, MA, USA; Chicago, IL, USA; Irvine, CA, USA; Kirkland, WA, USA; Los Angeles, CA, USA; Madison, WI, USA; New York, NY, USA; Palo Alto, CA, USA; Portland, OR, USA; Pittsburgh, PA, USA; Raleigh, NC, USA; Durham, NC, USA; Reston, VA, USA; Redmond, WA, USA; Redwood City, CA, USA; San Diego, CA, USA; Goleta, CA, USA; San Bruno, CA, USA; Seattle, WA, USA; San Francisco, CA, USA; San Jose, CA, USA; Santa Cruz, CA, USA; Sunnyvale, CA, USA; Washington D.C., DC, USA.

Minimum Qualifications:

• Currently pursuing a PhD degree in a quantitative discipline (e.g., statistics, biostatistics, physics, applied mathematics, operations research, economics).
• Experience with statistical methods (i.e., linear models, multivariate analysis, stochastic processes, sampling methods, etc.).
• Experience with statistical software (e.g., R, Python, MATLAB) and database languages (i.e., SQL).

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.
• Experience leveraging data insights into storytelling for business stakeholders.
• Experience in controlled experiment design and causal inference methods.
• Ability to prioritize requests and partner well in an environment with competing demands from stakeholders.

About the Job:

As a Business Data Scientist, you will be a subject matter specialist for translating business problems from your supported organization or functional area into analytical solutions and insights. You will provide technical mentorship in delivering project work including implementing data science solutions, improving data pipelines, developing evaluation metrics, or building statistical models that provide insights to the business. You will create and implement reused and scaled solutions within the team's development process. You will collaborate with supported teams and win stakeholder trust by translating business needs into tractable analyses or evaluation metrics. You will work closely with product and engineering teams to analyze impact on product or Google-wide metrics (including daily activities, retention, churn).

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.

The US base salary range for this full-time position is $113,000-$150,000. Our salary ranges are determined by role, level, and location. 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.
• Design and analyze controlled experiments or counterfactual causal inference studies to examine the incremental impact of Ads marketing programs.
• Interact cross-functionally, making 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.
• Develop and automate reports, and iteratively build and prototype dashboards to provide insights at scale, solving for business priorities.