Help define and build the data science models that predict human behavior and optimize the work environment for employee success
Research into the full-time employees of one the world’s fastest-growing and most global companies, acting as a thought leader in determining how we should model employee experiences, team interactions, and organizational engagement.
Use research methodologies to tackle abstract business problems with well-backed solutions, and bring tremendous enthusiasm to the challenge of better understanding human behavior.
Combine applied quantitative research with the messiness of employee data, behavioral theory, and human emotion
Master or PhD degree in a quantitative discipline (ideally in social science): Psychology, Statistics, Applied Mathematics, Computer Science, Engineering, Behavioral Economics, Biostatistics, etc.
2+ years experience deriving insights from large amounts of real, sparse heterogeneous data with a statistical programming language (e.g. Python, R), and/or SQL.
Experience in data mining, causal inference, experiment design, and/or machine learning techniques to solve real-world problems.
Able to translate business objectives into actionable analyses and communicate findings clearly to both technical and non-technical audiences.
Experience in people analytics or I/O psychology topics preferred.
Bias towards learning - always looking to find innovative solutions to problems that stretch your own abilities, but also willing to take the time to upskill those around you.