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People Analytics In Mountain View – Google Internship Programs – Google

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Job Description:


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 Ph.D.s in I/O Psychology, Organizational Behavior (micro & macro), Sociology, Social Psychology, Anthropology, Behavioral Economics, and related fields. To read more about some of our work, see a selection of our research here ( and check out this article in the New York Times Magazine (, this one in Slate Magazine (, or this one in The Atlantic (

Job 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.

Job Requirements/Qualifications:

  • Experience conducting applied research in organizations.
  • Topical experience in one of the following areas: performance management, individual and team-level performance and productivity, individual difference (e.g., personality traits, behaviors, well-being), DEI (diversity, equity, and inclusion), selection and assessment (including relevant psychometric methods), decision science and behavior change, or quantitative text analysis.
  • Experience with statistical analyses, including fundamentals (e.g., ANOVAs and/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.
  • Returning to a degree program after the internship ends.

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