Data Science Lead, People Analytics

Uber Overview

We are looking for a driven individual to build out and lead our People Data Science team. You and your team will define and build the data science models that predict human behavior and optimize the work environment for employee success as Uber continues to expand globally. Alongside the wider people analytics team, you’ll do 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.

The right person should have an advanced quantitative background, be comfortable enough with research methodologies to tackle abstract business problems with well-backed solutions, and bring tremendous enthusiasm to the challenge of better understanding human behavior. Qualified candidates should demonstrate past experience translating business objectives into specific data science initiatives and research projects with measurable and impactful outcomes. In addition, we’ll expect our Data Science Lead to possess both the strategic thinking needed to plan projects and the technical know-how to execute on those plans. Finally, this individual will be expected to closely partner with Software Engineering and PM teams to implement internal models & findings at scale.

In general, the ideal candidate is excited at the prospect of combining applied quantitative research with the messiness of employee data, behavioral theory, and human emotion. Ultimately, you care most about using data to develop the long-term strategies required to ensure Uber remains a great place to work!

Job Description


  • MS/PhD in a quantitative discipline: Statistics, Applied Mathematics, Computer Science, Machine Learning, Engineering, Behavioral Economics, Biostatistics, etc.
  • 5+ years experience deriving insights from large amounts of real, sparse heterogeneous data with Python, R, or other statistical packages.
  • Experience in people analytics or I/O psychology topics strongly preferred.
  • Strong statistical know-how – data mining, causal inference, time series, etc.
  • Experience in applying 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.
  • Research mindset – ability to structure a project from idea to experimentation to implementation.
  • 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.


  • Employees are given Uber credits every month
  • Ground floor opportunity with the team; shape the strategic direction of the company.
  • The rare opportunity to change the world such that everyone around you is using the product you built. We’re not just another social web app, we’re moving real people and assets and reinventing transportation and logistics globally.
  • Sharp, motivated co-workers in a fun office environment.


  • 401(k) plan, gym reimbursement, nine paid company holidays.
  • Full medical/dental/vision package to fit your needs.
  • Unlimited vacation policy; work hard and take time when you need it.

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