Uber is hiring for Associate Risk Analyst


 About Company:

Uber Technologies, Inc. (Uber) is an American mobility as a service provider. It is based in San Francisco with operations in approximately 72 countries and 10,500 cities. Its services include ride-hailing, food delivery , package delivery, couriers, freight transportation, electric bicycle and motorized scooter rental via a partnership with Lime, and ferry transport in partnership with local operators. Uber does not own any vehicles; instead, it receives a commission from each booking.

Job Role: Associate Risk Analyst

Job Location: Hyderabad

Package: 8.6 LPA

Qualification: Any Graduate from any stream

Batch: 2022/21/20/19/18/17

Experience: 0-2 yr

About the Role:

The analyst will be responsible for monitoring fraud trends around the world. This analyst will optimally analyze trends, and deploy recommendations and algorithms which require strong communication across product, engineering, data science, finance, and operations partners in a complex environment. As an owner of key fraud metrics, you should have the analytics experience, intellectual curiosity, and resourcefulness to identify, measure, and mitigate new and emerging loss vectors. In this role, you will require a mix of business and technical acumen and also strong cross-functional skills to communicate with various internal and external partners.

---- What You Will Do ----

  • This hands-on analytics role will be responsible for supervising Uber's Risk platform capabilities and developing new strategies to keep the fraudsters off Uber by identifying patterns using data analysis and visualization
  • You will serve as the subject matter authority on analytics/data-driven solutions that mitigate the risk of financial losses while also maintaining a positive user experience and enabling Uber to continue making big bold bets.
  • You will develop a solid understanding of key Uber systems and tools to optimally review and analyze emerging trends and provide recommendations for mitigating emerging fraud vectors.
  • Communicate optimally with cross-functional teams across subject areas such as product, engineering, data science with a focus on Risk/Fraud mitigation.





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