PhD Business Data Scientist Intern - Summer 2027

Google Inc.; Redmond (WA); On-site; USD 118,000 - 157,000; Full time

Benefits offered by this job

Health, dental, vision insurance

Sick Time: 40 hours/year (Seattle: 69)

Holidays: 13 paid days per year

Job summary

Google Inc. is seeking a Business Data Scientist Intern (PhD) for Summer 2027 in the United States. The role focuses on translating business problems into analytical solutions and building scalable data pipelines and models.

You will mentor teams and collaborate with product and engineering to measure impact on Google-wide metrics. Ideal candidates are pursuing a PhD in a quantitative field, proficient in statistics and data analysis, and experienced with R, Python, MATLAB, and SQL.

Qualifications

• Pursuing a PhD in a quantitative discipline (e.g., statistics, biostatistics, physics, applied mathematics, operations research, economics).
• Experience with statistical methods such as linear models, multivariate analysis, stochastic processes, or sampling methods.
• Experience with statistical software (R, Python, MATLAB) and SQL.

Responsibilities

• Translate business problems into analytical solutions and insights for supported teams.
• Build and evaluate data pipelines, metrics, and statistical models to inform decisions.
• Collaborate with product and engineering to analyze impact on product metrics and business outcomes.
• Develop and automate reports and dashboards to scale insights for stakeholders.
• Design controlled experiments or causal inference studies to assess initiatives.

Skills

Statistical methods

Data analysis

Storytelling with data

Education

PhD candidate

Tools

R

Python

MATLAB

SQL

Job description

Google Inc. is seeking a Business Data Scientist Intern (PhD) for Summer 2027 in the United States. The role focuses on translating business problems into analytical solutions and building scalable data pipelines and models.

You will mentor teams and collaborate with product and engineering to measure impact on Google-wide metrics. Ideal candidates are pursuing a PhD in a quantitative field, proficient in statistics and data analysis, and experienced with R, Python, MATLAB, and SQL.