Uber is looking to identify, understand, and scope emerging fraud trends across the platform and develop strategies to mitigate/stop fraudulent activities while preserving and improving the user experience.
Requirements
- Highly proficient in data science and visualization tools, such as SQL, Python, R, Tableau
- Proficient at defining, utilizing and communicating performance metrics.
- proven track record of applying analytical/statistical methods to solve real-world problems using big data
- Experience in framing ambiguous business problems into structured analytical work.
- Expertise in statistics and experimental design
Responsibilities
- Apply data analysis, experimentation, ML/LLM models to support the development of risk strategies and interventions while preserving and improving the user experience
- Evolve our risk metrics, shape and influence our data models and instrumentation to generate insights and develop new data products and models
- Communicate efficiently and present findings to the leadership team to strengthen business decisions.
- Deliver impactful and meaningful strategies to mitigate/stop fraudulent activities and achieve key results (OKRs)
- Participate in project definition and idea generation, work on collaborative projects with partners across the globe such as product, engineering, comm ops and regional teams with a focus on the Risk/Fraud mitigation
- Stay highly engaged and always hustle as Uber Risk is a very fast-paced environment
Other
- 5+ years in a data-focused role such as product analytics, business analytics, business operations, or data science
- Bachelor's degree in Mathematics, Statistics, Computer Science, Engineering, Economics or other quantitative fields
- Creative problem solving, critical thinking skills, and get things done attitude
- Hands-on, data-driven, and attentive to detail
- 3+ years in Risk/Fraud/Payments
