Decision Scientist for Risk and Fraud

Há 5 dias

Sao Paulo, Brasil Uber Tempo inteiro

**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. Collaborating with cross-functional teams comprising engineers, product managers, fellow decision scientists, and operations managers, you will be responsible for key performance metrics related to fraud detection and false positives optimization. Your analytical prowess and business acumen will be instrumental in driving data-informed decisions and shaping the future of risk management at Uber. 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

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