People Analytics Intern, PhD, Summer 2027

Location: Mountain View, CA, USA; Atlanta, GA, USA; Chicago, IL, USA; New York, NY, USA; San Francisco, CA, USA

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, 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.

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

US: $99000 - $132000 (USD) + 0% bonus target

Learn more about benefits at Google .

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.

Minimum qualifications

Currently enrolled in a PhD program in Industrial/Organizational Psychology, Organizational Behavior, Personality Psychology, Social Psychology or a related field.

Experience designing, developing, and conducting survey or experimental research.

Experience analyzing and manipulating data in R, Python, SQL, or other statistical programming languages.

Preferred qualifications

Currently attending a degree program in the US and available to work full time for 12 weeks outside of university term time.

Experience conducting applied research in organizations.

Topical experience in one of the following areas: performance management, individual and team-level performance and productivity, individual differences (e.g., personality traits, behaviors, well-being), selection and assessment (including relevant psychometric methods), decision science and behavior change, or quantitative text analysis.

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).

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).