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Staff Scientist - Reservations
About the Role
The Reservations data science team owns the experience and algorithms powering the Uber Reserve Product in the Rider and Driver app. We optimize the user experience for both Riders and Drivers, matching, dispatch and pricing algorithms, as well as growth levers to deliver magical experiences and business value.
The Reserve product is moving from a nascent mvp product to a more mature product, over the course of the last 3 years we have delivered on most of the “low hanging fruit” initiatives to improve the experience building levers to customize the product and handle edge cases to consistently deliver high reliability. Currently, our focus is shifting towards driving efficiency to improve our unit economics and to drive adoption and growth.
Some of the key projects involve major changes in Pricing, Matching and Dispatch that involve transitioning from heuristic based decision making to building machine learning models to make key decisions in real time, as well as important changes to Driver and Rider experience, including discoverability and awareness generation levers, and finally piloting new use cases that leverage the Reserve Tech as a platform to unlock new vectors of growth.
What you’ll do:
- Deploy a wide variety of methodologies, including causal inference techniques, funnel analyses, and econometric modeling to identify our largest business opportunities
- Work together with Product, Operations, and Engineering partners to design a roadmap of features and initiatives as well as the long-term team strategy
- Present findings to business and executive audiences
Basic Qualifications
- Ph.D., M.S. or Bachelor's degree in Statistics, Economics, Mathematics, Computer Science, Machine Learning, Operations Research, or other quantitative fields.
- Strong SQL skills and ability to code in either Python or R.
- Experience in experimental design and analysis (e.g., A/B and/or market-level experiments).
Preferred Qualifications:
- 6+ years of industry experience as a Data Scientist or equivalent.
- Ability to design, develop, productionize, and operate econometric models, experiments, and frameworks to assess challenging causal problems such as product incrementality and long-term value.
- Familiarity with pricing and elasticity modeling.
- Strong business and product sense: delight in shaping vague questions into well-defined analyses and success metrics that drive business decisions.
- Experience collaborating with very senior stakeholders (Director+) and generating insights to shape strategy.
- Familiarity with data visualization tools, such as Tableau.
For Seattle, WA-based roles: The base salary range for this role is USD$203,000 per year - USD$225,500 per year.
You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link .
Uber is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing .
Offices continue to be central to collaboration and Uber’s cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.
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, Veteran Status, or any other characteristic protected by law.
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