Business Data Scientist Intern

• 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, 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.
  
• Design and analyze controlled experiments or counterfactual causal inference studies to examine the incremental impact of business, product, or go-to-market initiatives. 

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.
• Proven track record of research published in ML/AI venues (e.g., NeurIPS, ICML, ICLR, KDD), with a focus on LLMs, generative AI, model evaluations, or related applied machine learning domains.
• Hands-on experience designing, training, and optimizing deep learning models, with prior research or internship experience applying ML/LLMs to real-world business challenges (e.g., recommendation systems, revenue forecasting, or agent development).
• Practical experience parsing, cleaning, and extracting structured insights from messy, unstructured text data (e.g., conversational transcripts, emails) and utilizing modern AI coding tools and agentic workflows (e.g., Cursor, Codex, Claude Code).
• Practical experience with time-series forecasting, standard econometric models, and analyzing experimental data using both frequentist and Bayesian statistical techniques.

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.

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

US: $118000 - $157000 (USD) + 0% bonus target

Learn more about benefits at Google.

Please complete your application before February 26, 2027.

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.
• Please ensure you’ve listed your anticipated graduation date (in MM/YY)
2. 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.

• 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).