Safeguarding the integrity of the Uber platform by identifying, analyzing, and mitigating emerging trends in fraud.
Requirements
- Minimum of 1 year of experience in a data-focused role, such as data science, analytics, management, or business intelligence
- Exceptional proficiency in and statistical analysis languages (SQL, R, or similar)
- Proven track record of leveraging advanced analytical techniques and statistical methods to solve complex, real-world problems
- Experience in hypothesis testing and statistical modeling
- Expertise in defining, measuring, and communicating performance metrics that drive business impact
- Data engineering/pipeline creation experience
- Familiarity with statistical optimization under unsupervised learning, boosted trees, neural networks, or natural language processing architectures.
Responsibilities
- Perform statistical analysis to understand behaviours and contribute to detection 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 using the full variety of statistical learning solutions
- Effectively communicate findings to drive business decisions
Other
- Collaborating with cross-functional teams of engineers, product managers, fellow decision scientists, and operations managers
- With guidance from manager, define and develop an area of expertise
- A natural problem-solver with a passion for critical thinking and a "get things done" mindset
- Good communication skills and the ability to articulate technical concepts to diverse stakeholders
- Comfortable with ambiguity and capable of thriving in a dynamic, self-directed environment
