Data Scientist

Uber
San Francisco, United StatesPosted 5 March 2026

Job Description

Data Scientist Department: Data Science Team: Data Scientist Location: San Francisco, United States Type: Full-Time **About the Role** We are looking for an exceptional Data Scientist with 3+ years of experience to help Uber’s internal and external applications, products and services to grow adoption, improve CSAT and reduce cost. You will leverage analytics, engineering, and machine learning, and data science to empower data-driven decision making in the full lifecycle of product development. You will be responsible for building this program from the ground up: partner with stakeholders, understand all aspects of the products, interact with cross-functional business and technical teams, predict risks, improve strategic decisions, and lead experimentation/growth projects. **What the Candidate Will Need / Bonus Points** \-\-\-\- What the Candidate Will Do ---- 01. Apply your expertise in quantitative analysis, data mining, and statistical modeling to deliver impactful, objective, and actionable data insights that enable informed business and product decisions 02. Define, measure, and analyze business metrics and product KPIs 03. Create tableau dashboards and the underlying data aggregations in GCP. 04. Conduct exploratory analysis to inform product strategy and evaluate recently released or existing products or features 05. Partner with multiple team members to make data-driven decisions across the organization by leveraging descriptive and predictive analytics 06. Work from the inception of a specified business problem identified by data to delivery of a solution, identify opportunities to fix or improve processes that make Uber better in the long term 07. Put together seemingly disparate pieces of data, build out the data pipeline and create interactive dashboards, provide comprehensive analytics support to partner teams, primarily through development of self-serve tools (such as Tableau and Looker) 08. Write queries, contribute to larger-scale products/projects and perform ad hoc analyses as needed, apply a diverse set of techniques including statistics, quantitative reason
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