Jobs
About the Role
At Uber, we empower people to earn and transact on the platform and to do this across the globe for millions of customers, we need to be compliant with local regulations and manage the risk that is associated with fraud losses. The Risk Intelligence team is responsible for keeping the platform safe from fraud losses while minimizing friction to legitimate customers. This team drives scalable solutions to address latest modus operandi driving losses while ensuring frictionless experience for legitimate users. We aim to maintain losses below the targetand create magical customer experiences by leveraging data and technology to capture insights, identify opportunities, and ultimately prioritize product and engineering initiatives.
Does this sound exciting to you? Are you a tested teammate, strategic problem solver, and executor? We want to hear from you.
---- What the Candidate Will Do ----
- Own the loss metrics for the assigned line of business/Region and design logics and scalable solutions to mitigate fraud causing modus operandi
- Own new risk solution and related experimentation including plan creation, roll-out, and monitoring
- Be an invaluable partner to cross-functional teams such as engineering, product management, various data teams to deploy data quality across critical pipelines and to set up processes to triage data issues
- Develop and track metrics and reporting functions to measure and monitor risk products on our platform
- Effectively and proactively communicate insights and drive projects to drive towards team goals
- Proactively seek out opportunities to build new solutions to tackle Risk
---- Basic Qualifications ----
- 3+ years of experience in a risk-focused role such as product analytics, business analytics, business operations, or data science
- Education in Engineering, Computer Science, Math, Economics, Statistics or equivalent experience
- Experience in modern programming languages (Matlab, Python) or statistical languages (SQL, SAS, R)
- Past experience with a Product / Tech company serving millions of customers on multiple platforms and countries
---- Preferred Qualifications ----
- SQL mastery. Write efficient and complex code in SQL
- Experience in Python/R and experimentation, A/B testing, and statistical modelling
- Experience in Risk in a Product / Tech company
- Proven ability to handle and visualise large datasets, explore and utilize raw data feeds
- Love of data - you just go get the data you need and turn it into an insightful story.
- A well-organized, structured approach to problem-solving
- Strong sense of ownership, accountability, and entrepreneurial spirit
- Great communicator, problem-solver & confident in decision making
- Independent & autonomous, while still a strong teammate
- Enthusiastic, self-starting and thrives in changing, agile environments
- Liaise with Product and engineering counterparts to launch and impact new products
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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About Uber

Uber
PublicUber develops, markets, and operates a ride-sharing mobile application that allows consumers to submit a trip request.
10,001+
Employees
San Francisco
Headquarters
$120B
Valuation
Reviews
3.7
10 reviews
Work-life balance
3.2
Compensation
4.0
Culture
4.1
Career
3.4
Management
2.8
68%
Recommend to a friend
Pros
Good compensation and pay
Flexible hours and schedule
Great team culture and colleagues
Cons
Long hours and tight deadlines
High pressure and stressful environment
Poor management and lack of support
Salary Ranges
15,354 data points
Junior/L3
Mid/L4
Senior/L5
Staff/L6
Junior/L3 · Data Scientist L3
0 reports
$145,456
total per 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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