Scientist II, Marketplace; Teams

About The Role

End-to-end product development from data analytics, modeling and experimentation perspective. Specifically, formulating ambiguous business problems, prototyping various machine learning & optimization & causal inference & marketplace dynamics models, producing data insights, and designing & analyzing experiments.

• We are hiring for multiple teams*

We are building the future of Uber's mobility and logistics platforms. Our teams drive innovation across critical areas including:

• Delivery Marketplace : A central pillar of Uber's delivery products, serving as the "brain" of the operation. We drive every decision that enables orders to go from point A to point B - from Uber Eats & Grocery, to newer verticals like Uber Direct and Connect. We're responsible for running an efficient marketplace with dispatch & pricing decisions.
• Maps :
  Building the geospatial technologies for all of Uber, including travel time prediction (ETA), routing, search & ranking, pickup & dropoff recommendation, and trip intelligence. The outputs power marketplace systems like pricing & matching and the core trip experience.
• Uber One Membership :
  Enhancing user experience and growth for Uber One, a fast-growing program providing members with exclusive benefits, best prices, and priority across the platform.
• Experimentation Platform :
  Building the experimentation platform and the underlying measurement models at Uber, providing reliable, trustworthy and agile experimentation and experiment analysis to power business decisions across the entire Uber ecosystem.
• Autonomous Mobility & Delivery (AM&D) :
  Pioneering the integration of autonomous vehicles into the existing ecosystem, tackling the complex challenge of building a reliable, efficient, and scalable hybrid marketplace for both Rides and Eats.

• Solve ambiguous, challenging business problems using data-driven approaches including ML, Optimization, Causal Inference.
• Develop and implement statistical / econometric methodologies to improve results validity, power and generalizability.
• Develop data-driven business insights and work with cross-functional customers to find opportunities and recommend prioritization of product, growth, and optimization initiatives.
• Design and analyze experiments, present results that provide actionable recommendations.
• Orient the teams around data-driven product development by driving the creation of logging, metrics, data visualization and diagnostic tools, and experimentation paradigms.
• Define how our teams measure success, by developing metrics, in close partnership with cross functional partners.
• Owning the product development cycle end to end from data and science aspects.

• Ph.D., M.S. or Bachelor's degree in Economics, Statistics, Machine Learning, Operations Research, or other quantitative fields.
• 2+ years of industry experience as an Applied or Data Scientist or equivalent (not required with Ph.D.).
• Background in at least one programming language (eg. Python, R, Java, Ruby, Scala/Spark or Perl)
• Ability to use Python or similar technologies to work efficiently with large data sets and prototype algorithms & models
• Coding and SQL proficiency and ability to develop statistical analysis and algorithm prototyping in Python or R.
• Design experiments and interpret the results to draw detailed and actionable conclusions across a variety of key performance indicators.

• Ph.D. in Economics, Statistics, Machine Learning, Operations Research or other quantitative fields.
• Excellent communication and collaboration skills:
  Able to lead initiatives across multiple product areas and communicate findings with leadership and product teams.
• Experience in leading key technical projects and substantially influencing the scope and output of others.
• Thought leadership to drive multi-functional projects from concept to production.
• Experience in large-scale marketplace algorithm design, membership / consumer growth, or experimentation platform.
• Experience with exploratory data analysis, statistical analysis and model development.
• Strong programming skills to prototype models in at least one of Python (preferably), R, Java, Go, Scala.