About the Role
Uber has taken a strategic bet on partnering with third-party micromobility providers to offer riders more transportation options on our platform. As Data Science/Analyst Lead for Uber's Micromobility team, you'll lead a team to help define Uber's strategy for bikes & scooters and launch new product experiences to shape the urban transportation space.
You'll work with design, engineering, product, and business teams to first determine how third-party micromobility partners will integrate with Uber. As you understand your customer base, you'll develop and launch differentiated experiences in cities all over the world that allow riders to discover, book, and ride micrombility options seamlessly through the Uber app.
This team will host entrepreneurial attitude which will focus on rapid experimentation of ideas to expand the product portfolio for Uber. This team is working to bring customer-centric micromobility experience to our riders, at par with the Uber experience that they have come to expect. We are looking for a high performing Data Scientist/Analyst to make significant contributions to our mission. A deep analytical passion to learn and ability to execute on key business priorities is a must.
As Data Scientist/Analyst for the team, you will play the very meaningful role of helping define the product vision and deliver it from ground-up by working with a very fast paced and passionate team of high-performing Product Analysts, Data Scientists, Engineers, Designers, Product managers, and Ops Managers. People with entrepreneurial bent of mind, independent analytical thinking, rapid hypotheses building, testing hypotheses using experimentations, and aid the team make informed decision and deliver high business impact are desired characteristics for this role!
What You'll Do
You will shape the direction of Uber's products by using data-driven insights to identify opportunities and prioritize of product and engineering initiatives. You will:
• Perform \"deep-dive\" analysis across all areas of our business to drive growth strategies, including product development and rider engagement strategies
• Generate ideas for exploratory analysis to shape future projects and provide recommendations for actions
• Perform variety analyses, hypothesis testing, and causal analyses to statistically assess relative impact and extract trends
• Build models to enhance understanding of user behaviour and predict future performance of cohorts
• Design experiments and interpret the results to draw detailed and measurable conclusions
• Create dashboards and reports to regularly communicate results and monitor key data metrics
• Present findings to senior management to inform business decisions
• Collaborate with cross-functional teams across fields such as product, engineering, operations, and marketing.
What You'll Need
• Undergraduate and/or graduate degree in Math, Economics, Statistics, Engineering, Computer Science, or other quantitative field
• 6+ proven experience as a Data Science/Product Analytics or other forms of data analysis
• Excellent SQL skills and experience in at least one scripting language (Python or R preferred)
• Demonstrated ability to use data to help solve business problems
• Solid understanding of statistical methods and experiment designs
• Ability to learn and adapt to new methodologies and approaches to data collection and data analysis
• Ability to deliver on tight timelines and move quickly with cross-functional teams to execute on decisions while maintaining attention to detail
• Ability to work in a self-guided manner
• Good communication and organization skills
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 10,000 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.