PhD Data Scientist Intern: Business Analytics

Socket.dev; Mountain View (CA); On-site; USD 118,000 - 157,000; Part time

Job summary

Google in Mountain View, CA is seeking a Business Data Scientist to translate business problems into analytical solutions and insights. You will mentor on data science projects, improve data pipelines, develop evaluation metrics, and build scalable models that inform product and Google-wide decisions.

You will collaborate with product and engineering teams to analyze impact on product metrics, including daily activity, retention, and churn, while delivering reusable analyses and dashboards.

Qualifications

• Currently pursuing a PhD 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 statistical software (R, Python, MATLAB) and database languages (SQL).

Responsibilities

• Work with large complex data sets, solve difficult non-routine analysis problems, and apply advanced analytical methods.
• Build and prototype analysis pipelines iteratively to provide insights at scale.
• Interact cross-functionally, making business recommendations with effective presentations of findings.
• Develop and automate reports, and prototype dashboards to provide insights at scale.
• Design and analyze controlled experiments or counterfactual causal inference studies.

Skills

Statistical methods

Education

PhD candidate in quantitative field

Tools

SQL

R

Python

MATLAB

Job description

Google in Mountain View, CA is seeking a Business Data Scientist to translate business problems into analytical solutions and insights. You will mentor on data science projects, improve data pipelines, develop evaluation metrics, and build scalable models that inform product and Google-wide decisions.

You will collaborate with product and engineering teams to analyze impact on product metrics, including daily activity, retention, and churn, while delivering reusable analyses and dashboards.