Sr Scientist, Tech - Science

About the role

As a Senior Scientist working on Earner Program Logistics, you will solve high-stakes optimization and marketplace problems at the boundary of digital algorithms and physical-world delivery. Operating as a technical multiplier, you will shape the science strategy for core marketplace decisions—ensuring algorithms optimize for long-term platform value and are incentive compatible.

In this role, you will support the end-to-end scientific vision for complex logistics systems, partnering with teams across all of Uber to build a balanced, resilient, and highly efficient marketplace for eaters, merchants, and couriers globally.

What you’ll do

• Translate strategically important, unstructured problems into rigorous experiments and productionized solutions that move the needle for the Uber Eats business.
• Drive the end-to-end product development lifecycle from a science and data perspective, solving business challenges using Causal Inference and Optimization.
• Set the science strategy and experimentation standards across multiple teams, ensuring scientific rigor and driving organization-wide adoption of best practices.
• Act as a technical multiplier , identifying opportunities for better performance, efficiency, and reduction of technical debt in models and processes.
• Influence executive-level roadmaps by presenting complex technical findings and long-term strategic recommendations to senior leadership.
• Own the technical trajectory of critical product areas, ensuring solutions are designed to be extensible, modular, and observable while balancing short-term needs and long-term productivity.

Basic Qualifications 

• Ph.D., M.S. or Bachelor's degree in Statistics, Machine Learning, Operations Research, Economics, Mathematics, Computer Science, or other quantitative fields.
• 5+ years of industry experience as an Applied or Data Scientist or equivalent (or 3+ years with a Ph.D.).
• Proficiency in at least one programming language (eg. R, Python, Java, Ruby, Scala/Spark or Perl).
• Experience designing experiments and interpreting results across a variety of key performance indicators.

Preferred Qualifications

• Ph.D. degree in a quantitative field such as Machine Learning, Operations Research, or Statistics.
• Outstanding communication skills with a track record of influencing leadership and technical teams through storytelling and data-driven insights.
• Experience leading high-complexity technical projects and substantially influencing the scope and output of others.
• Proven ability to work efficiently with large-scale datasets (e.g., 100M+ rows) using Spark, Hive, or HDFS.
• Thought leadership to drive multi-functional projects from initial concept to production.