Google People Analytics - PhD Internships

Google People Analytics- Social Science-  PhD Internship - Summer 2016
Sunnyvale, California
Timeframe: Summer 2016 (10-12 weeks)
Application Deadline: January 19th, 2016


Job Description: We are looking for an enthusiastic, creative, and curious mid- to advanced-level PhD student enrolled in a program in Industrial/Organizational Psychology, Organizational Behavior, Personality Psychology, Social Psychology, Strategy, Management, Sociology, Behavioral Economics or a related field to join us on Google’s People Analytics team for the summer. 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 employee development, leadership, hiring, personality, teams, decision making, and longitudinal data analysis. We have strong research backgrounds, with PhDs in I/O Psychology, Organizational Behavior (micro & macro), Behavioral Economics, Anthropology, Sociology, and related fields. Our intern will take an active role in conducting academically rigorous research on a broad array of issues facing Google. To read more about some of our work, check out this article in Slate Magazine (, or this one in The Atlantic (

Interested candidates please submit the following to Dr. Carrie Ott-Holland at

  1. Cover letter describing why you are interested in our internship and how your research, work, and extracurricular experience will help you fulfill the specific responsibilities listed below (PDF preferred).

  2. Resume or CV including current research topics, statistical skills, experience analyzing survey data, relevant work experience, and recent publications/presentations (PDF preferred).

  3. Fill out and submit this form.


Intern 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.

  • Conduct advanced statistical analysis (e.g., correlation, regression, factor analysis, t-test, ANOVA, SEM, LASSO, random forests) using survey and archival data.

  • Communicate findings and recommendations to influence leaders to take action on the results.

  • Write research briefs.



  • Educational background -- Mid- to advanced-level PhD student who has completed at least three years of study, is post-comprehensive exams, but has not completed dissertation (i.e., has not graduated and will not be graduating prior to October 2016). PhD student should be enrolled in a program in Industrial/Organizational Psychology, Organizational Behavior, Personality Psychology, Social Psychology, Management, Strategy, Sociology, Behavioral Economics, or a related field.

  • Statistical skills -- Strong statistical skills (e.g., ability to conduct correlations, regressions, factor analyses, t-tests, ANOVAs, network analysis, LASSO, HLM, or other models; experience with Structural Equation Modeling preferred)

  • Research experience -- Experience designing, developing, implementing, and analyzing data from rigorous survey and experimental research

  • Work experience -- Demonstrated skills related to internal consulting, client management, and project management

  • Problem-solving -- Ability to creatively solve problems in a fast paced, rapidly changing environment

  • Communication -- Ability to communicate effectively, and especially to succinctly translate technical information for a non-technical audience

  • Technical skills -- Proficiency in spreadsheets, SPSS, R, STATA, and/or other statistical languages

  • Passion -- Strong interest in conducting research in an applied setting and developing internal consulting skills

  • Authorization to work in the U.S. -- Students who are not U.S. citizens are not eligible for this internship (unless they are attending a school in the U.S. and can apply for CPT).


Preferred but not required:

  • Workplace research -- Experience conducting research on topics relevant to organizations

  • Surveys -- Experience designing and analyzing data from longitudinal survey research

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