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Marketplace Fraud Manager
Mexico City, Mexico; Santiago, Chile; São Paulo, Brazil
·
On-site
·
Full-time
·
1mo ago
Benefits & Perks
•Comprehensive health, dental, and vision insurance
•Professional development budget
•Generous paid time off and holidays
•401(k) matching
•Team events and activities
•Healthcare
•Learning
Required Skills
React
Python
PostgreSQL
About the Role
As a Marketplace Fraud Manager, you'll play a key role in safeguarding the integrity of our platform by building and improving processes to detect, prevent, and reduce marketplace abuse across all Delivery business lines.
You'll partner closely with cross-functional teams-including Product, Risk, Legal, and Operations, both regionally and centrally-to define and enforce policies, lead thorough investigations, and use data to uncover trends and address fraud at scale. Your work will directly influence how we create a safer, more trustworthy experience for all platform users.
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What You'll Do
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Monitor Trends: Analyze marketplace data to identify emerging abuse patterns and potential risks.
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Solve Complex Problems: Use a data-driven approach to detect unusual behavior, recommend solutions, and evaluate the best course of action.
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Implement Prevention Strategies: Design and execute scalable processes that reduce fraudulent activity and protect platform integrity.
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Collaborate Across Teams: Partner with Product, Legal, Operations, and Customer Support teams to align efforts and continuously improve fraud prevention mechanisms.
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What You'll Need Basic Qualifications
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Experience: a minimum of 3 years of experience solving complex analytical problems-ideally in tech, consulting, or a data-driven role.
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Analytical Skills: Proven ability to analyze large datasets to identify trends and generate actionable insights.
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Problem-Solving Mindset: Strong critical thinking skills with a structured, data-informed approach.
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Adaptability: Comfortable working in a fast-paced, evolving environment with shifting priorities.
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Technical Proficiency: Experience using tools such as SQL, Python, or similar for data analysis.
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Communication: Professional fluency in English and the ability to communicate clearly across functions and levels.
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Bonus Points
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Degree in a technical or analytical field such as Computer Science, Mathematics, Statistics, or Business Administration.
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Experience leading large-scale, cross-functional projects in international environments.
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Advanced proficiency in Python and libraries like pandas.
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Familiarity with data visualization tools like Tableau, Looker Studio, or Streamlit.
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
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
Mid/L4
Mid/L4 · Data Analyst
3 reports
$209,300
total / year
Base
$161,000
Stock
-
Bonus
-
$203,580
$209,300
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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