Uber's Risk Engineering team needs to address complex problems in risk and fraud domains by building cutting-edge real-time fraud detection and prevention systems that scale to millions of users leveraging large scale data, distributed systems, and advanced machine learning technologies.
Requirements
- Deep technical expertise and proven technical leadership/technical influence across wide organization
- Previous experience with Risk, Fraud Detection
- Experiences with Applied Machine Learning
- Strong analytical and problem-solving skills.
- Demonstrated ability to contribute to long term technical vision, to scope, create and successfully deploy new technical strategies / initiatives / capabilities.
Responsibilities
- Design and develop scalable solutions to address fraud and abuse problems as well as drive better user experiences across Uber Products and Lines of Businesses
- Work with cross functional teams (Product Managers, Data Scientists/Analysts, Program engineers, Machine Learning Engineers) to identify any product/functionality gaps, define the problem space, contribute to product requirements, design and develop system solutions.
- Contribute to longer term technical roadmap and drive overall system architecture betterment for Risk product Engineering.
- Identify systemic opportunities and preempting architectural risks before these become bottlenecks.
- Provide thought leadership including challenge the status quo when needed.
- Lead the problem identification and formulation, software design and architecture, and guide cross-functional product and engineering teams to deliver high impact technology solutions to address complex problems in risk and fraud domains.
- Foresee architectural problems and opportunities within the organization and lead the technical direction for long term system architecture betterment and modernization.
Other
- 10+ years experience.
- Capable of creating structure and driving progress in an ambiguous environment
- Team player with good communication skills.
- Experience to interact with cross-functional teams from multiple geo-locations
- Mentor, coach, and multiply: proactively mentor senior engineers and influence teams across the broader Risk
