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| Job Location | Bengaluru/ Bangalore (Karnataka) |
| Education | Any Graduate |
| Salary | As per Industry Standards |
| Industry | Consumer Durables/FMCG, Warehousing |
| Functional Area | IT Software : Software Products & Services |
| EmploymentType | Full-time |
Want to join a team that saves tens of millions of dollars per year for Amazon, and uses technology, including machine learning and statistical modeling techniques, data mining and big data analytics, cloud computing services, and highly available/scalable distributed systems that support hundreds of millions of transactions across the globe We have an exciting opportunity within the Abuse Prevention team to architect and build the next generation of engineering systems to address abuse of Amazons customer-first policies that will impact multiple Amazon businesses across the globe.About the Amazon Buyer Risk Prevention Team:The BRP (Buyer Risk Prevention) team has a worldwide reputation as the #1 in eCommerce Fraud and Abuse Prevention. Trust and Safety of our customers comes first. Always! We thrive on maintaining the highest bar of customer experience while we deliver on those tenets.The Buyer Abuse Engineering Team, a group within BRP, strives to protect Amazon businesses exposed to customer abuse while maintaining the highest level of customer experience for our good customers. This means building highly sophisticated, data-centric systems that can detect abusive patterns across millions of transactions.We build highly scalable, flexible and distributed systems that utilize the power of data at every step - compute predictive variables, build models using machine learning algorithms and plug into different pipelines to prevent abusive transactions from taking place. As Amazon businesses grow and abusers morph to find new ways to take undue advantage of our liberal policies, our engineers and data scientists are constantly innovating to stay ahead of the game and protect Amazon and our customers.LocationsIND, KA, Bengaluru
Keyskills :
machine learning data mining big data analytics cloud computing distributed systems algorithms