About the Role:

At Uber, People Analytics drives business performance by translating employee insights into strategic action. We partner with senior leaders to improve organizational effectiveness, employee engagement, and long-term workforce outcomes across the full talent lifecycle-from hiring to retention.

We are looking for a data scientist who combines strong quantitative rigor with a deep interest in human behavior. This role sits at the intersection of business analytics consulting and employee listening, shaping company-wide decisions through advanced analytics, survey insights, and behavioral data.

Role and Responsibilities:

Drive company-level workforce strategy

1. Lead high-impact analytics that inform strategic decisions on engagement, retention, performance, and organizational health
2. Translate ambiguous business questions into structured analytical frameworks and measurable outcomes

Apply advanced quantitative methods to people data

1. Use statistical modeling, causal inference, experimentation, and/or machine learning to understand employee behavior and outcomes
2. Work with messy, real-world people data and integrate multiple data sources (survey, HRIS, behavioral data)

Evolve employee listening analytics

1. Analyze Uber-wide survey data and behavioral signals (e.g., organizational network analytics)
2. Improve measurement approaches (survey design) and uncover actionable insights on employee experience

Influence stakeholders at all levels

1. Communicate complex findings clearly to both technical and non-technical audiences
2. Act as a thought partner to senior leaders, shaping decisions with data-backed recommendations

What the Candidate Will Need / Bonus Points
---- Basic Qualifications ----

1. Master's or PhD in a quantitative field (e.g., I/O Psychology, Organizational Behavior, Behavioral Economics, Statistics, Data Science, or related)

Proficiency in SQL:

1. 2+ years of industry experience using Python or R to analyze large-scale datasets

---- Preferred Qualifications ----

1. PhD with 1+ years, or MS with 3+ years of experience in applied research or data science (ideally in a fast-paced, tech environment)
2. Strong foundation in statistical modeling, causal inference, experimentation, and/or machine learning
3. Background in people analytics, HR data, or behavioral science applications
4. Experience with survey design and measurement, and/or organizational network analysis (ONA)
5. Demonstrated ability to leverage GenAI tools to automate, augment, or scale data analysis, insight generation, or research workflows

• For San Francisco, CA-based roles: The base salary range for this role is USD**$142,000 per year**
• USD**$158,000 per year**.

You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.

Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.

Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.

Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.