Scientist II, Tech - Science

About the role and team

Working in Science at Uber means solving complex, real-world problems that don't always have a textbook solution. You will be part of a team that turns massive amounts of data into actionable insights, influencing everything from marketplace efficiency to user experience. In this role, you’ll be a technical "detective," unpicking data-driven puzzles in a high-stakes, fast-moving environment. You’ll thrive here if you stay calm under pressure, embrace the "messy" reality of imperfect datasets, and have the grit to move projects from hypothesis to production.

This is a role for an owner who is energized by the challenge of building at scale. You will navigate the ambiguity of shifting priorities and internal complexity, ensuring that our data-driven products are robust, reliable, and grounded in sound statistical principles. If you're sharp, steady, and motivated by meaningful impact at global scale this is where you’ll grow.

What you’ll do

• Develop data-driven insights and collaborate with cross-functional partners: Product, Engineering, and Operations to identify opportunities and prioritize optimization initiatives.
• Build statistical and machine learning models to provide strategic insights and real-time production enhancements to global products.
• Design and analyze experiments using A/B testing and causal inference, presenting results that provide actionable recommendations for product growth.
• Drive technical excellence by creating logging, metrics, and diagnostic tools that orient our teams around data-driven product development.
• Define success metrics in close partnership with stakeholders to ensure our teams are measuring impact accurately and consistently.
• Navigate technical debt and scale, ensuring our models and data pipelines are designed to be extensible and observable as the business evolves.

Basic Qualifications

• Ph.D., M.S., or B.S. degree in Statistics, Computer Science, Applied Mathematics, Electrical Engineering, Economics, or other quantitative fields.
• If M.S. degree, a minimum of 2+ years of industry experience required; if B.S. degree, a minimum of 3+ years of industry experience required.
• Proficiency in at least one programming language (e.g., Python or R) for statistical analysis and algorithm prototyping.
• Experience working with large-scale datasets (SQL, Python, Spark, or similar) to solve complex business problems.
• Proven ability to design experiments and interpret results to drive actionable conclusions.

Preferred Qualifications

• Exceptional Communication Skills: A track record of conveying complex technical findings in a manner that is easy for marketers and non-technical partners to understand.
• Systems Thinking: Demonstrated ability to understand customer problems and translate them into robust system designs and model architectures.
• Technical Resilience: Experience solving strategically important problems in high-ambiguity environments, often without a predefined playbook.
• Operational Excellence: Familiarity with Spark, Hive, or HDFS for handling 100M+ scale datasets in production.