HubMub
-
Uber

Data Scientist - Fraud

Uber
Brazil · Full-time · Not Applicable
About The Team

DS team is spread across US, Amsterdam, Brazil, and India and is primarily focused on managing global losses across LoBs with real-time strategies. We balance loss rate with action rate to both make attackers pursue other avenues and allow good affected users to have proceed.

The key questions we ask ourselves daily: "How exactly did this attacker bypass our layered defence?" and "What is the best sustainable way to prevent this from scaling?"

We run product rollouts (e.g. a new user challenge or a new kind of actioning) and implement models built by MLEng.

What The Candidate Will Need / Bonus Points

---- What the Candidate Will Do ----

  • Perform statistical analysis to understand behaviours and contribute to detection models/features
  • Build and maintain rules to address evolving fraudulent activities
  • Extract insights from large datasets to develop fraud mitigation strategies
  • Build deep understanding of data, reporting, and key metrics
  • Conduct to and optimize mitigation solutions
  • Collaborate with global cross-functional teams on prevention projects
  • Effectively communicate findings to drive business decisions
  • With guidance from manager, define and develop an area of expertise

---- Basic Qualifications ----

  • Immediate availability to work from São Paulo;
  • English proficiency (B2+);
  • Advanced proficiency in SQL;
  • Experience in a data-focused role, such as data science, analytics or management;
  • Proven track record of leveraging advanced analytical techniques and statistical methods to solve complex, real-world problems;
  • Expertise in defining, measuring, and communicating performance metrics that drive business impact;
  • Excellent communication skills and the ability to articulate technical concepts to diverse stakeholders;
  • Prior experience in testing, and statistical modeling its a plus;
  • Familiarity with Python or R.

---- Preferred Qualifications ----

  • Advanced degree in a quantitative field such as Statistics, Mathematics, Operations Research, Economics, or a related discipline
  • Data engineering/pipeline creation experience
  • Prior background in risk, fraud, or payments

Key Skills

Ranked by relevance

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Posted
Nov 24, 2024
Type
Full-time
Level
Not Applicable
Location
Greater São Paulo Area
Company
Uber

Industries

Internet Marketplace Platforms

Categories

Engineering Information Technology

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