People Analytics Intern, PhD, Summer 2025

ding relevant psychometric methods), decision science and behavior change, or quantitative text analysis.

• Experience with statistical analyses, including fundamentals (e.g., ANOVAs or regressions) and with one or more advanced approaches (e.g., factor analysis, network analysis, HLM, SEM).

• Experience using R for statistical analysis and data visualization.

• Experience in SQL or other scripting languages and experience with future proofing code to be long lasting (e.g. detailed documentation).

About the job

We are a group of social scientists who conduct experimental, survey, and archival research to inform people-related business decisions. Example content areas include, but are not limited to: decision making, DEI (diversity, equity and inclusion), leadership, employee well-being, hiring, performance management, performance development, personality, longitudinal data analyses, and social networks. We have strong research backgrounds, with PhDs in I/O Psychology, Organizational Behavior (micro & macro), Sociology, Social Psychology, Anthropology, Behavioral Economics, and related fields.
The US base salary range for this full-time position is $92,000-$109,000. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. 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 the People Analytics team to design and implement new studies, analyze data and report on results of research initiatives to a business audience.
• Communicate findings and recommendations to influence leaders to take action on the results.
• Write research briefs.
• Conduct statistical analysis (e.g., correlation, regression, factor analysis, T-test, ANOVA) using survey and archival data with analyses conducted in R.