Jobs

Senior Scientist - UberEats Courier Pricing
New York, NY; San Francisco, CA
·
On-site
·
Full-time
·
1mo ago
Compensation
$183,000 - $183,000
Benefits & Perks
•Professional development budget
•Team events and activities
•Generous paid time off and holidays
•Parental leave
•Comprehensive health, dental, and vision insurance
•Flexible work arrangements
•Learning
•Parental Leave
•Healthcare
•Flexible Hours
Required Skills
React
Python
JavaScript
About the Role
The Uber Eats Marketplace team is the heart of the Uber Eats business. We build the platform and products that power the magical experience of connecting eaters, couriers, and restaurants. As a critical component of this ecosystem, the Courier Pricing team is responsible for the complex systems that determine courier earnings on every Uber Eats delivery worldwide.
Our mission is to build and refine a fully automated pricing system that optimizes our three-sided marketplace for consumers, couriers, and merchants. We leverage sophisticated optimization, machine learning, and causal inference techniques to balance efficiency, reliability, and cost under highly dynamic conditions. This is a high-impact team solving core business challenges across diverse verticals-including restaurant delivery, grocery, and retail-and supporting global markets with unique and complex problems.
---- What You Will Do ----
- Own the end-to-end lifecycle of scientific models and algorithms, from ideation and development to deployment and iteration, tackling our most complex pricing challenges.
- Act as a thought leader, influencing the product and technical roadmap by identifying new opportunities and translating them into actionable scientific projects.
- Lead the design and analysis of large-scale experiments, pushing the boundaries of causal inference to measure the impact of our pricing strategies and deliver actionable insights.
- Drive collaboration with senior stakeholders across Product, Engineering, and Operations, effectively communicating complex findings and presenting strategic recommendations to leadership.
- Mentor and guide junior scientists on the team, elevating the overall technical bar and fostering a culture of scientific rigor.
---- Basic Qualifications ----
- A Ph.D. in a quantitative field (e.g., Statistics, Economics, Computer Science, Operations Research) with 2+ years of industry experience, OR a Master's/Bachelor's degree in a similar field with 5+ years of relevant industry experience.
- Deep, hands-on expertise and a proven track record of applying advanced methods from machine learning, statistics, optimization, and causal inference to solve complex, real-world business problems.
- Proven experience leading complex, cross-functional projects, with a track record of influencing the technical direction and output of the team.
- Proficiency in modeling, data analysis, and programming using a language like Python or R.
- Experience querying databases using SQL.
- Excellent communication and presentation skills, with the ability to influence both technical and non-technical audiences.
---- Preferred Qualifications ----
- Expert-level knowledge in one or more of the following areas: experimental design, causal inference, machine learning, economics, or optimization, with a track record of designing and implementing model architectures and algorithms.
- Direct experience in a marketplace-related problem space, especially pricing optimization.
- Proven ability to design and analyze large-scale experiments to inform critical pricing and product decisions.
- Experience working with large datasets using distributed computing systems like Spark, Hive, or Presto.
- For New York, NY-based roles: The base salary range for this role is USD**$183,000 per year**
- USD**$203,000 per year**.
- For San Francisco, CA-based roles: The base salary range for this role is USD**$183,000 per year**
- USD**$203,000 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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