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.

Rate of Pay: $225,077 to $270,092 per Year

You will be eligible to participate in Uber's bonus program, and may be offered other types of comp. You will also be eligible for various benefits. More details can be found at the following link https://www.uber.com/careers/benefits.

What you’ll do

• Use data to understand product performance and to identify improvement opportunities.
• Build statistical, optimization, and machine learning models for a range of applications in the pricing and incentives algorithms space.
• Design and execute product experiments and interpret the results to draw detailed and actionable conclusions.
• Present findings to senior management to inform business decisions.
• Collaborate with cross-functional teams across disciplines such as product, engineering, operations, and marketing to drive system development end-to-end from ideation to productionization.
• May telecommute.
  

Basic Qualifications

• Employer will accept a Master's degree in Statistics, Engineering, Computer Science, Operations Research, or related field and 3 years of experience in the job offered or in a related occupation.
• Position requires:
  • Data manipulation and data visualization, ability to handle large-scale and unstructured data, experienced in data manipulation and transformation, generate informative data visualization to uncover underlying trends/insights, and build customer-facing dashboards (e.g.Tableau, looker) to power self-serve insights;
  • Analytical skills using proven business frameworks (SWOT analysis, balanced scorecard, benchmarking, and competitive analysis) and effective root-cause analysis;
  • Mathematical and statistical analysis, ability to translate data-driven insights into understandable visuals for senior management, and application of statistical experimentation methods (e.g., time series evaluation, difference-in-difference method, and synthetic control method);
  • Machine learning modeling, ability to build scalable ML models end-to-end, predicting business outcomes and enabling downstream business decisions;
  • Causal inference, ability to leverage causal inference models to infer incrementality from observational data and build trust from stakeholders on those lift estimates;
  • Optimization and simulation, ability to simulate different scenarios (e.g. user distribution and competitor strategies) and design optimization framework to inform business decisions;
  • Python and SQL in data extraction and modeling, has experience with database system designing and data modeling implementation (eg, designing and deploying data pipelines), and can independently translate innovative algorithms into production-ready modular codes;
  • Experience with the GIT version control system.

Ready to Ride?