Senior Manager - Data Science
About the Role
We're looking for a seasoned risk professional to lead Uber's risk analytics team. Uber enables billions of ride around the world every year, and it is critical for us to manage the risks associated with the payments, MarketPlace abuses, and account security for all our users. We are pioneering new techniques and technologies everyday to detect and counter bad actors all over the world who are constantly adapting and discovering new ways to abuse our platform.
Uber is at the forefront of one of the most exciting marketplace challenges as the world rapidly evolves from desktop to on-demand mobile commerce. Our ability to effectively deal with risk in this environment is key to our ongoing improvement and allows the company to make bold bets while maintaining an enjoyable and painless customer experience. It's our job to think about this so that our community of riders and drivers don't have to.
As the head of this function, you'll lead a skilled team of data analysts and data scientists and fully own the business results, optimizing for the balance between risk mitigation and user experience.
The role requires excellent people leadership to build, develop and lead the cross functional team. An ideal candidate should possess a deep technical background in risk management, paired with business intuition and a passion for customer experience. We believe that people are one of the most important assets to Uber and because of that we foster an environment that is welcoming to diverse perspectives.
What you'll do
- Define the vision and strategy, and set challenging goals for the risk analytics team
- Interact with a wide group of stakeholders to guide and manage broader priorities for our payment and fintech products
- Develop advanced risk capability using rich data and complex machine learning algorithm to accurately detect risk
- Design effective actions to mitigate payment risk while balancing the frictions for good users
- Collaborate closely with PMs, engineers, Risk Ops, and external vendors to build innovative solutions
What you'll need
- A master's degree or equivalent in quantitative or engineering discipline.
- At least 10+ years of experience in managing fraud risk, familiar with payment world
- Excellent leadership skills with at least 5-7 years of people management experience
- Advanced analytical skills connected with excellent business instincts to "connect the dots"
- High standards for excellence across the board - from your own contributions to the people you work together with to the products you collaborate on
- A ""driver"" personality. A bias toward action, great collaborator and skilled disambiguator/simplifier - constantly fostering clarity and delivery
- Grittiness - You don't hesitate to take initiative and address something hands-on, you persevere when others give up
- Ability to take initiative with data - you just go get the data you need with no muss/fuss and can turn it into a thoughtful story. You know how to leverage data to make decisions without getting stuck in paralysis by analysis
- User-centered attitude - examples from your past of tough product challenges that you persevered through because you were unwilling to make your problems your users' problems
- True passion for Uber's mission and the company's hybrid technology / operations nature
- A never-ending desire to grow and learn
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 600 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.
At Uber we don’t just accept difference—we celebrate it, we support it, and we thrive on it for the benefit of our employees, our products and our community. Uber is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.