About the Role
Earners (drivers and couriers) are an integral part of Uber's multi-sided marketplace. They provide the time and the means to move people and things. Importantly, they enable the connection between the physical and digital world to make the movement happen at the push of a button for everyone, everywhere.
Within Uber, Earner Access plays a critical role in earners' journey as the team is responsible for earner onboarding, activation, early life cycle, and resurrection. This presents the teams with the opportunity to shape and tailor the product experience during earners' many firsts (i.e., first time interacting on the Uber platform, choosing the earning opportunity, going online, receiving incentive offers, completing a trip, or reading the earnings summary). These firsts can be daunting.
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Therefore, making sure that the earner journey is great at every touch point is important to build trust with Earners, communicate Uber's value proposition, and ensure each firsts to be a great experience.
What You'll Do
- Deploy a wide variety of methodologies, including advanced experimentation and econometric modeling, to evaluate technical, product, and business decisions
- Design and execute product experiments and interpret the results to draw detailed and actionable conclusions
- Work together with Product, Operations, and Engineering partners to design a roadmap of features and initiatives and shape long-term 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 another quantitative field
- 2+ years of industry experience as an Applied or Data Scientist or equivalent
- Design experiments and interpret the results to draw detailed and actionable conclusions across a variety of key performance indicators
- Ability to use SQL, and Python or R (or similar technologies), to work efficiently with large datasets
- Experience working with cross-functional teams(product, science, product ops etc)
Preferred Qualifications
- Excellent communication skills: able to lead initiatives across multiple product areas and communicate findings with leadership and product teams
- Experience leading key technical projects and substantially influencing the scope and output of others
- Knowledge of experimental design and analysis or experience with exploratory data analysis and model development
- Experience communicating qualitative research methods and findings to non-qualitative researchers
- Expert in one of the following areas: A/B experimentation design, causal inference, machine learning, economics, or optimization
For New York, NY-based roles: The base salary range for this role is USD$155,000 per year - USD$172,000 per year.
For San Francisco, CA-based roles: The base salary range for this role is USD$155,000 per year - USD$172,000 per year.
For Seattle, WA-based roles: The base salary range for this role is USD$155,000 per year - USD$172,000 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.