Decision Scientist for Risk and Fraud - Sao Paulo, Brasil - Uber

Uber

Empresa verificada

Sao Paulo, Brasil

há 3 semanas

Postado por:

Ana Silva

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Descrição

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 crossfunctional 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 datafocused 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, realworld 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 problemsolver with a passion for critical thinking and a "get things done" mindset
Comfortable with ambiguity and capable of thriving in a dynamic, selfdirected 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