招聘
About the Role
The Core Analytics & Science Team (CAS) is Uber's primary science organisation, covering both our main lines of business as well as the underlying platform technologies on which those businesses are built. We are a key part of Uber's cross-functional product development teams, helping to drive every stage of product development through data analytic, statistical, and algorithmic expertise. CAS owns the experience and algorithms powering Uber's global Mobility and Delivery products. We optimise and personalise the rider experience, target incentives and introduce customizations for routing and matching for products and use cases that go beyond the core Uber capabilities.
What the Candidate Will Need / Bonus Points
---- What the Candidate Will Do ----
- Refine ambiguous questions and generate new hypotheses about the product through a deep understanding of the data, our customers, and our business
- Design experiments and interpret the results to draw detailed and impactful conclusions.
- Define how our teams measure success, by developing Key Performance Indicators and other users/business metrics, in close partnership with Product and other subject areas such as engineering, operations and marketing
- Collaborate with applied scientists and engineers to build and improve on the availability, integrity, accuracy, and reliability of data logging and data pipelines.
- Develop data-driven business insights and work with cross-functional partners to find opportunities and recommend prioritisation of product, growth, and optimisation initiatives.
---- Basic Qualifications ----
- Undergraduate and/or graduate degree in Math, Economics, Statistics, Engineering, Computer Science, or other quantitative fields.
- 4+ years experience as a Product Analyst, Sr. Data Analyst, or other types of data analysis-focused functions
- Excellent understanding of statistical principles backed by an academic foundation
Advanced SQL expertise:
- Experience with either Python or R for data analysis
- Significant experience in setting up and evaluation of complex experiments
- Proven track record to wrangle large datasets, extract insights from data, and summarise learnings/takeaways.
- Experience with Excel and some dashboarding/data visualisation (i.e. Tableau, Mixpanel, Looker, or similar)
---- Preferred Qualifications ----
- Proven aptitude toward Data Storytelling and Root Cause Analysis using data
- Ability to learn and adapt to new methodologies for data collection and analysis
- Ability to deliver on tight timelines and prioritise multiple tasks while maintaining quality and detail
- Ability to work in a self-guided manner
- Ability to mentor, coach and develop junior team members
- Superb communication and organisation skills
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 fuelds progress. What moves us, moves the world - let's move it forward, together.
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.
Accommodations may be available based on religious and/or medical conditions, or as required by applicable law. To request an accommodation, please reach out to accommodations@uber.com.
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3.1
10 reviews
Work Life Balance
4.2
Compensation
2.3
Culture
3.5
Career
2.0
Management
2.5
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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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