About the role and team Working in Science at Uber means solving complex problems in a high-stakes, fast-moving environment. You’ll turn massive amounts of unstructured data into focused plans of execution, navigating ambiguity to build technologies that directly influence every decision made in our marketplace. This isn't just about building models; it’s about making smart decisions with imperfect information and owning the outcomes in an environment where speed and scale can't be separated. In this role, you’ll be the bridge between technical depth and business impact, solving messy, high-priority problems that don’t always have a textbook solution. You’ll thrive here if you possess an owner’s mindset, stay calm under pressure, and have the grit to drive projects through their entire lifecycle from idea inception to production. We’re looking for someone who thinks critically and moves with urgency to shape the future of how people and things move in the real world. What you’ll do • Develop data-driven business insights by collaborating across disciplines: product, engineering, and operations to identify growth opportunities and recommend prioritization of high-impact initiatives. • Build and scale statistical, optimization, and machine learning models that provide both strategic insights and real-time production enhancements to global products. • Design and analyze complex experiments using A/B testing and causal inference to provide results that drive critical decision-making. • Unblock technical barriers by driving the creation of logging, metrics, and diagnostic tools that orient teams around data-driven product development. • Define how teams measure success by developing robust metrics in close partnership with cross-functional stakeholders to align on long-term impact. • Lead through influence by effectively communicating complex technical findings and outcomes to leadership and technical partners. Basic Qualifications • Ph.D., M.S. or Bachelor's degree in Statistics, Machine Learning, Operations Research, Economics, Mathematics, Computer Science, or other quantitative fields. • 7+ 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.