About the Role
The Consumer Pricing & Incentives DS team uses data to improve and automate all aspects of Uber's core mobility and delivery products, as we drive growth, retention, engagement, and affinity on the Uber platform. This includes providing insight into how pricing, surge and incentives is working and offering opportunities for improvement; understanding consumer adoption and engagement and identifying opportunities for product evolution; designing and analyzing experiments to understand the effects of pricing changes and/or incentives on rider and eater behaviors/conversion/engagement.
What the Candidate Will Do
- Refine ambiguous questions and generate new hypotheses about the product through a deep understanding of the data, our customers, and our business
- Design experiments and interpret the results to draw detailed and impactful conclusions
- Define how our teams measure success, by developing Key Performance Indicators and other user/business metrics, in close partnership with Product and other subject areas such as engineering, operations and marketing
- Collaborate with applied scientists and engineers to build and improve on the availability, integrity, accuracy, and reliability of data logging and data pipelines
- Develop data-driven business insights and work with cross-functional partners to identify opportunities and recommend prioritization of product, growth, and optimization initiatives
Want more jobs like this?
Get Data and Analytics jobs delivered to your inbox every week.
Basic Qualifications
- B.S or M.S. in Math, Economics, Bioinformatics, Statistics, Engineering, Computer Science, or other quantitative field
- If M.S. degree, at least 2 year of industry experience as a Product Data Scientist or equivalent
- If B.S., at least 3 years of industry experience as a Product Data Scientist or equivalent
- Experience in experimental design and analysis, exploratory data analysis, and statistical analysis
- Proficiency in SQL
- Strong communication skills across technical, non-technical, and executive audiences
Preferred Qualifications
- 4+ years of industry experience
- Advanced analytics skills such as causal inference and non-standard A/B testing techniques
- Ability to use Python/R to work efficiently at scale with large data sets for data manipulation and visualization
- Experience with dashboard/data visualization toolings
- Basic knowledge of algorithm and model development
For New York, NY-based roles: The base salary range for this role is USD$165,000 per year - USD$183,000 per year.
For San Francisco, CA-based roles: The base salary range for this role is USD$165,000 per year - USD$183,000 per year.
For Seattle, WA-based roles: The base salary range for this role is USD$165,000 per year - USD$183,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD$165,000 per year - USD$183,000 per year.
For all US locations, 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 https://www.uber.com/careers/benefits.
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 this form.
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.