Team Lead Manager - Risk Strategy Analytics at Uber
Risk Data Science and Analytics teams provide insights and develop machine learning models and strategies to combat payment fraud and marketplace abuse, improve account security and integrity, and minimize credit risk for financial products.
About the Role
We're looking for a Manager, Risk Strategy Analytics to join our Risk Strategy Analytics team to apply a data-driven approach to identify, understand, and scope emerging fraud trends on Uber platform. In this role you'll lead a group of Risk strategy analysts and work closely with a cross-functional team consisting of engineers, product managers, operations, and other data scientists and analysts. This role will be responsible for key performance metrics such as fraud losses, false positives, and operational efficiency. You will require a mix of business and technical acumen and also cross-functional skills to communicate with various internal and external stakeholders.
What You'll Do
- Lead teams to achieve key results (OKRs) and deliver impactful and meaningful strategies to mitigate/stop fraudulent activities
- Use data and models to support the development of risk mitigation strategies and interventions while preserving and improving the user experience
- Participate in project definition and idea generation, work on collaborative projects with partners across the globe such as product, engineering, comm ops and data science with a focus on the Risk/Fraud mitigation
- 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.
- Stay highly engaged and always hustle as Uber Risk is a very fast-paced environment
- 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
- Experience in either managing teams or leading large cross functional projects
- Highly proficient in data analysis 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
- Creative problem solving, critical thinking skills, and get things done attitude
- Hands-on, data-driven, and attentive to detail
- Advanced degree in Mathematics, Statistics, Computer Science, Economics or other quantitative fields
- 3+ years in Risk/Fraud/Payments
- 1+ years leading teams
- Expertise in statistics and experimental design
- Demonstrated ability to be an effective leader, producing high-quality work and crafting meaningful relationships
- Team player -- this is a highly collaborative function that will work with a range of senior leaders
- Outstanding communication and people skills -- numbers are key but one should be able to explain the implications to an executive audience
- Passion for Uber!
At Uber, we ignite opportunity by setting the world in motion. We take on big problems to help drivers, riders, delivery partners, and eaters get moving in more than 10,000 cities around the world.
We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have the curiosity, passion, and collaborative spirit, work with us, and let's move the world forward, together.
Uber is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.