Data Scientist, Product Intern, MS, Summer 2027

Mountain View, United StatesOn-SiteInternshipPosted 3d ago

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Job description

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Please complete your application before October 9, 2026.

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 Master's 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):

In the “Resume Section:” attach an updated CV or resume.

Please ensure you’ve listed your anticipated graduation date (in MM/YY)

In the “Education Section:” attach a current or recent unofficial or official transcript in English.

Under “Degree Status,” select “Now attending” to upload a transcript.

In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based Interns. Benefits for this role include:

Health, dental, vision insurance
Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
Holidays: 13 paid days per year

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

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.

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; South San Francisco, CA, USA; Sunnyvale, CA, USA; Washington D.C., DC, USA.

Minimum qualifications:

Currently pursuing a Master's degree in a quantitative field (e.g., Statistics, Computer Science, Engineering, Mathematics, Data Sciences, etc.).
Experience working with statistical packages (e.g., R, SAS, Stata, MATLAB, etc.).
Experience articulating product questions, pulling data from datasets (SQL), and using statistics to arrive at an answer.

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 articulating product questions, pulling data from datasets (SQL or Python), and using statistics to arrive at an answer.
Ability to translate analysis results into business recommendations.
Interest and ability to work with data, metrics, analysis and trends and applied knowledge of measurement, statistics and program evaluation.
Excellent problem-solving, written/verbal communication, and business judgment skills.

About the job

In the Data Scientist product role, you will provide quantitative analysis, market expertise and a strategic perspective to our partners throughout the organization. As a member of the team, you'll serve as an analytics expert for your partners, using numbers to help them make better decisions. You will weave stories with meaningful insight from data. You'll make key recommendations for Googlers in Engineering and Product Management.

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.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $94000 - $125000 (USD) + 0% bonus target

Learn more about benefits at Google.

Responsibilities

Conduct data analysis to make business or product recommendations (i.e., cost-benefit, invest-divest, forecasting, impact analysis).
Deliver effective presentations of findings and recommendations to multiple levels of stakeholders, creating visual displays of quantitative information.
Collaborate with cross-functional stakeholders to understand their business needs, formulate and complete analysis that includes data gathering, analysis, ongoing scaled deliverables and presentations.
Help Google to focus on key decisions to improve products and services.

Job details are sourced from the employer's original posting.

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