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Staff Scientist, Rider Booking Experience
New York, NY; San Francisco, CA; Seattle, WA
·
On-site
·
Full-time
·
1mo ago
Compensation
$216,000 - $216,000
Benefits & Perks
•Professional development budget
•Generous paid time off and holidays
•401(k) matching
•Flexible work arrangements
•Comprehensive health, dental, and vision insurance
•Learning
•Flexible Hours
•Healthcare
Required Skills
Node.js
Python
JavaScript
About the Role At Uber, our mission is to reimagine how the world moves for the better. As part of the Rider Booking Experience team, you'll have the opportunity to work on the core mobility business and influence the experience for millions of riders. From optimizing AI Booking experiences to shaping executive-level strategy for the mobility product portfolio, your work will have a meaningful impact on the future direction of Uber. You'll design experiments, develop models, and analyze user behavior to drive growth in the mobility business.
The data science work we do is diverse and helps to drive every stage of product development. Our toolkit includes experimentation, product analytics, and ML modeling. You will collaborate with other scientists, product managers, and business teams to understand the challenges in our space, then tackle problems that no one else has solved yet.
Some of the key projects will include evaluating AI booking agents, building targeting models for messaging in the app, and running large scale experiments to improve the UX. In this role, you'll have exposure to many of the teams within Uber and an opportunity to influence the strategy for a core pillar of Uber's business.
What You'll Do:
Drive Strategic Vision:
- Shape the vision for the mobility booking experience and translate the strategy into measurable goals, robust models, and scalable systems.
- Propose and defend data-driven hypotheses in senior and executive reviews; shape long-term product direction with clear narratives and analysis.
Modeling, Metrics & Experimentation
- Design and scale advanced machine learning and optimization systems to power steps in the booking flow.
- Establish key success metrics and measurement frameworks for features and launches.
- Incubate 0-to-1 solutions to evaluate and iterate on emerging AI user experiences.
Cross-Functional Leadership
- Partner deeply with engineering, product, and operations to identify impactful opportunities and co-drive execution from inception to delivery.
- Act as a scientific thought leader, mentoring junior scientists and influencing technical strategy across the organization.
Basic Qualifications:
- Ph.D. or equivalent experience in a quantitative field such as Economics, Statistics, Machine Learning, or Applied Mathematics.
- Minumal 4 years of industry experience in Data Science, Applied Science, or related roles, with a proven record of driving product impact.
- Deep expertise in SQL, Python, and statistical analysis.
- Advanced knowledge of experimentation and causal inference methodologies.
- Experience presenting to and influencing senior leadership and executives.
Preferred Qualifications:
- Minumal 7 years experience in fast-paced tech or marketplace environments; experience in AV mobility or delivery domains is a plus.
- Proven experience building and deploying ML or optimization models in production.
- Demonstrated leadership of large-scale, cross-functional technical initiatives.
- Entrepreneurial experience launching new product lines, systems, or 0-to-1 initiatives.
- Strong product and systems thinking, comfortable making trade-offs between ideal science and product reality.
- Strong communication, storytelling, and influencing skills.
- For New York, NY-based roles: The base salary range for this role is USD**$216,000 per year**
- USD**$240,000 per year**.
- For San Francisco, CA-based roles: The base salary range for this role is USD**$216,000 per year**
- USD**$240,000 per year**.
- For Seattle, WA-based roles: The base salary range for this role is USD**$216,000 per year**
- USD**$240,000 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's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.
Uber is proud to be an Equal Opportunity 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.
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About Uber
Reviews
3.1
10 reviews
Work Life Balance
4.2
Compensation
2.3
Culture
3.5
Career
2.0
Management
2.5
45%
Recommend to a Friend
Pros
Flexible hours and schedule
Meeting different people and cultures
Make your own hours
Cons
Inconsistent and low pay
Safety concerns with passengers
Traffic and difficult drivers
Salary Ranges
23,534 data points
Junior/L3
Mid/L4
Senior/L5
Staff/L6
Junior/L3 · Data Scientist L3
0 reports
$145,456
total / year
Base
-
Stock
-
Bonus
-
$123,638
$167,274
Interview Experience
5 interviews
Difficulty
3.0
/ 5
Duration
14-28 weeks
Offer Rate
40%
Experience
Positive 80%
Neutral 20%
Negative 0%
Interview Process
1
Application Review
2
Online Assessment
3
Recruiter Screen
4
Technical Phone Screen
5
Case Study/Analytics Test
6
Final Loop/Panel Interview
7
Offer
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Case Study
Technical Knowledge
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