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About the Role
Uber Marketplace is at the core of Uber's business, and Marketplace Matching is a strategically critical component of Marketplace. The mission of the team is to foster growth and increase profitability of Uber by pushing the frontiers of machine learning, data science and economics and developing highly reliable and scalable platforms to accelerate Uber's impact on the transportation industry.
This role will drive high-impact projects to optimize rider & driver matching at Uber using optimization, machine learning, and causal inference. We are looking for individuals who not only excel in problem solving and critical thinking, but also are interested and proficient in writing production code, converting ideas to scalable systems.
- What the Candidate Will Do
- Build elastic, scalable, and fault-tolerant distributed machine learning libraries and systems used to power machine learning development productivity across Uber.
- Work closely with engineers in the broader Uber ML/AI Platform Team (Michelangelo) to improve the broader ML Platform ecosystem for our users.
- Work closely with Uber's ML community (with ML Engineers, Data Scientists, and Researchers) to scope and build new abstractions for scalable machine learning.
Basic Qualifications:
- PhD or equivalent in Computer Science, Engineering, Mathematics or related field
- Programming language (e.g. C, C++, Java, Python, or Go)
- 5+ years of proven experience in the industry
- Large-scale training using data structures and algorithms
- Modern machine learning algorithms (e.g., tree-based techniques, supervised, deep, or probabilistic learning)
- Machine Learning Software such as Tensorflow/Pytorch, Caffe, Scikit-Learn, or Spark MLLib
Preferred Qualifications:
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Causal ML
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Reinforcement learning
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Contextual bandit models
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Personalization and ranking experience
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8-10+ years of proven experience in the industry
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For San Francisco, CA-based roles: The base salary range for this role is USD**$232,000 per year**
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USD**$258,000 per year**.
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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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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