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# Data Scientist, People Analytics

- **Company:** Uber
- **Location:** San Francisco, CA, United States
- **Salary:** $142,000.0 - $158,000.0
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Big Data, Network Analysis, Human Resources Information System (HRIS), HR Analytics, Python (Programming Language), Machine Learning, Generative AI
- **Published:** May 19, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=278dda1f8bd79eae

## About the Role

* Master's or PhD in a quantitative field (e.g., I/O Psychology, Organizational Behavior, Behavioral Economics, Statistics, Data Science, or related)
 * Proficiency in SQL2+ years of industry experience using Python or R to analyze large-scale datasets, * PhD with 1+ years, or MS with 3+ years of experience in applied research or data science (ideally in a fast-paced, tech environment)
 * Strong foundation in statistical modeling, causal inference, experimentation, and/or machine learning
 * Background in people analytics, HR data, or behavioral science applications
 * Experience with survey design and measurement, and/or organizational network analysis (ONA)Demonstrated ability to leverage GenAI tools to automate, augment, or scale data analysis, insight generation, or research workflows

## Description

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

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

Apply advanced quantitative methods to people data

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

Evolve employee listening analytics

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

Influence stakeholders at all levels

 * Communicate complex findings clearly to both technical and non-technical audiencesAct as a thought partner to senior leaders, shaping decisions with data-backed recommendations


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