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Sr Data Scientist - Driver Vehicles (Seattle)

undefined, Data Science in Seattle, WA

At Uber, we ignite opportunity by setting the world in motion. We take on big problems to help drivers, riders, delivery partners, and eaters get moving in more than 600 cities around the world.


We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have the curiosity, passion, and collaborative spirit, work with us, and let’s move the world forward, together.

About the Role


The Driver team at Uber is focused on accelerating driver growth, engagement, and retention across 300+ cities worldwide. Data Scientists on Driver play a central role in guiding product development and strategy through the discovery of insights from data. In this position, you will offer a data-driven perspective and work closely with product, engineering, and marketing. You will be on the forefront of analysis and leverage our data sources to propose new ideas related to every area of our product, including developing predictive models of driver behavior, studying market balance and developing a growth model in the context of a two-sided market, creating experiment designs for product changes with difficult constraints (e.g. extensive product network effects). Our team's autonomy gives us the flexibility to focus on the highest-impact projects in this adaptive and challenging role as we bring increasing numbers of riders and drivers onto the Uber platform.


Driver Vehicles is part of the Driver team, fully based in Seattle. Vehicles is a big force to Uber global traffic, and it also plays a critical role in Driver growth. Duties in Vehicles DS team cross entire DS territory including machine learning, economics, optimization, experiment, data engineering, business intelligence, customer intelligence, and data visualization.

What you'll do


  • Leverage data to perform intensive analysis across all areas of our business to catalyze product development
  • Apply economics, optimization and machine learning techniques to solve incentives, scheduling, and other real-world complex problems
  • Perform time-series analyses, hypothesis testing, and causal analyses to statistically assess the relative impact and extract trends
  • Design experiments and interpret the results to draw detailed and actionable conclusions
  • Create models to enhance understanding of user behavior and predict future performance of cohorts
  • Generate and execute on ideas for exploratory analysis to shape future projects and provide recommendations for actions
  • Define KPIs, create dashboards and reports to regularly communicate results by building data pipeline and monitoring data quality
  • Collaborate with cross-functional teams across disciplines such as product, engineering, operations, and marketing

What you'll need


  • At least 5 years of working experience in a quantitative analysis role, senior DS preferred
  • Master's degree in Economics, Operation Research, Statistics, Computer Science, Physics, or other quantitative fields. Econ background preferred
  • Ability to write code and contribute to a code base in Python or R
  • Experience writing and understanding complex SQL; experience working with large datasets
  • Experience in experimentation - A/B, sequential and multi-armed bandit, practical A/B testing experience preferred
  • Good understanding of machine learning and statistical modeling
  • Collaborate closely with cross-functional teams to execute on decisions
  • Excellent communication and presentation skills
  • Experience in customer engagement preferred


See our Candidate Privacy Statement

At Uber we don’t just accept difference—we celebrate it, we support it, and we thrive on it for the benefit of our employees, our products and our community. Uber is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.