** Hiring for multiple positions and levels **
Want to join a team that saves tens of millions of dollars per year for Amazon, and uses cutting edge 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 Amazon’s customer-first policies that will impact multiple Amazon businesses across the globe.
About the Amazon TRMS and Abuse Prevention Teams:
The TRMS (Transaction Risk Management Systems) 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 Abuse Prevention Team, a group within TRMS, 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.
· At least a bachelor degree in computer science or equivalent.
· Outstanding expertise in C++ or Java and object-oriented design.
· A solid understanding of databases (relational and/or NoSQL).
· A strong background in algorithms and data structures.
· A focus on clean code and solid designs.
· A strong Linux (or UNIX) background.
· Experience with machine learning techniques.
· Experience with large-scale multi-tiered systems and service-oriented architecture.
· Experience with scripting languages such as Perl or Ruby