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Senior Scientist, Delivery (Multiple Teams)
San Francisco, CA; Sunnyvale, CA
·
On-site
·
Full-time
·
4d ago
About the Role
Scientists at Uber use data to improve and automate all aspects of Uber's core rideshare and delivery products. You will be joining the Delivery team, which owns all aspects of our delivery experience - from eaters, couriers to merchants!
We are looking for experienced candidates with a passion for solving new and difficult problems with data. In this role, you will be able to utilize your strong quantitative skills to improve the Uber delivery experience as well as the overall marketplace performance.
About the Team (We are hiring for multiple teams)
We are building the most preferred online delivery platform globally and driving innovation across a number of areas including:
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Fulfillment: Delivery is the core of our product. We carefully refine a living and breathing marketplace to balance long run outcomes with the everyday experiences of our customers and couriers.
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Consumer:** We help users all over the world find what they need on Uber Eats. To do so we build state of the art recommendation systems and novel user experiences to help users discover the selection around them.**
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Ads:** Ads is one of the fastest growing lines of businesses at Uber. We work on end-to-end experience across lines of business, from enrolling advertisers, to designing auction and bidding, and integrating ads into the user experience.**
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Offer:** We optimize merchant offers, by identifying the optimal selection to make the platform affordable to consumers, by innovating on pricing models to align incentives, and by maximizing return for merchants through targeting.**
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Merchant:** Dedicated to optimizing merchant experience and driving merchant success at every stage of their lifecycle. We drive strategic and product decisions that expand merchant selections and maximize the value merchants bring to our marketplace.**
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What You'll Do
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Solve ambiguous, challenging business problems using data-driven approaches, including ML, Optimization, and Causal Inference.
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Develop and implement statistical/econometric methodologies to improve results validity, power and generalizability.
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Develop data-driven business insights and work with cross-functional customers to find opportunities and recommend prioritization of product, growth, and optimization initiatives.
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Design and analyze experiments, present results that provide actionable recommendations.
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Orient the teams around data-driven product development by driving the creation of logging, metrics, data visualization and diagnostic tools, and experimentation paradigms.
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Define how our teams measure success, by developing metrics, in close partnership with cross-functional partners.
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Owning the product development cycle end-to-end from data and science aspects.
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Basic Qualifications
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Ph.D., M.S., or Bachelors degree in Statistics, Economics, Operations Research, or other quantitative fields.
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Minimum 4 years of industry experience as an Applied or Data Scientist or equivalent (2+ years if holding a Ph.D.)
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Experience in experimental design and analysis, exploratory data analysis and statistical analysis.
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Ability to use Python/R to work efficiently at scale with large data sets.
Preferred Qualifications:
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Experience managing projects across large, ambiguous scopes and driving initiatives in a fast moving, cross-functional environment.
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Expertise in synthesizing complex technical analyses into clear insights to influence product direction.
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Excellent communication skills across technical, non-technical, and executive audiences.
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Experience within a Delivery or Ecommerce business.
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For New York, NY-based roles: The base salary range for this role is USD**$190,000 per year**
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USD**$211,000 per year**.
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For San Francisco, CA-based roles: The base salary range for this role is USD**$190,000 per year**
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USD**$211,000 per year**.
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For Sunnyvale, CA-based roles: The base salary range for this role is USD**$190,000 per year**
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USD**$211,000 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. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/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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