Uber Decision Scientist Risk Fraud 

United States, West Virginia 

779905930

About the Role

Join our team as a Risk Decision Scientist and play a crucial role in safeguarding the integrity of the Uber platform. In this global position, you will leverage your data-driven expertise to identify, analyze, and mitigate emerging fraud trends. Through statistical analysis and creative problem-solving, you will contribute to the development of robust strategies that minimize fraud losses while ensuring operational efficiency and a seamless user experience.

While experience with machine learning techniques is a valuable asset, this role primarily focuses on statistical analysis, fraud detection, and risk management rather than specific model development or deployment.

What You'll Do:

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

What You'll Need:

• Immediate availability to work from São Paulo
• English proficiency (B2+)
• Minimum of 5 years of experience in a data-focused role, such as data science, fraud analytics, risk management, or business intelligence
• Exceptional proficiency in SQL and statistical analysis languages (Python, R, or similar)
• Proven track record of leveraging advanced analytical techniques and statistical methods to solve complex, real-world problems
• Experience in experimentation, A/B testing, and statistical modeling
• 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
• A natural problem-solver with a passion for critical thinking and a "get things done" mindset
• Comfortable with ambiguity and capable of thriving in a dynamic, self-directed environment

Bonus Points If You have:

• 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

* 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 .