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Data Science Manager - JUMP Hardware

Engineering in San Francisco, CA

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 Data Science Manager (DSM) will demonstrate leadership in developing, standardizing and communicating hardware quality related metrics and insights to optimize fleet performance for the next generation electric sharing vehicles. In this role, the DSM play a central role in guiding product development, fleet maintenance strategy, evaluation of failure risk using statistical models through the discovery of insights from data. The role utilizes expertise to solve problems, develop and execute objectives for self and others, and drive data-driven perspective while working closely with quality, engineering, operations, and supply chain teams. This is an exciting time to be part of the newly created Mobility team focused on unique mobility product offerings - electric bikes & scooters. The DSM will be at the forefront of analysis and leverage our data sources to propose new ideas related to every area of our product, including developing predictive models. We are rapidly growing so that we can efficiently and effectively validate our products for safety and reliability to improve the customer experience and in doing so, continue our leadership position in defining the product quality standards for a sharing industry.

What You’ll Do
  • Leverage data to perform intensive analysis across all areas of our operations to catalyze product performance, reduce product failures and the cost of poor quality
  • Create models to enhance understanding of failure trends, product performance and predict future performance of vehicles to improve availability and reliability  
  • Perform time-series analyses, hypothesis testing, and causal analyses to statistically assess the relative product failure impact and extract trends to determine component life cycles across multiple markets
  • Design experiments and interpret the results to draw detailed and actionable conclusions to optimize CapEx and OpEx
  • Propose KPIs, create dashboards and reports to regularly communicate hardware performance by building data pipeline and monitoring quality
  • Establish standard work and performance metrics to drive operational excellence to support long-term business goals

 

What You’ll Need
  • 7 years of experience with quality and reliability engineering

 

About the Team

JUMP is building the future of urban mobility: shared electric bikes that are the quickest, most enjoyable, and most empowering way to get around a city. Cheaper than most public transit and faster than cars in traffic, JUMP e-bikes radically improve local transportation. Founded in 2010, JUMP pioneered dockless bike share and has deployed more than 15,000 bikes in 6 countries. Our goal is to transform cities, making them more sustainable, equitable, and livable through electric mobility. Recently acquired by Uber, our next step is to scale what we’ve done 100x - and launch electric bike sharing systems in every major city, globally. To make this vision a reality we need to grow our team. We place tremendous value on our company’s roots and culture: a mix of ingenuity, controlled chaos, hard work, and sense of purpose. This is a great opportunity to join a small but rapidly growing team that is shaping the future of transportation.


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.