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.
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.
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).