About the team... Amazon.com's Transaction Risk Management (or TRMS) protects the Amazon bottom line by preventing the bad guys from entering the front door. We've got the latest in machine learning algorithms, statistical modeling techniques and investigation tools but we need your help to keep Amazon.com safe. About the role... A software engineer with a security background who understands threat vectors around fraudulent and abusive attacks, and how the bad guys try to attack large sites like Amazon.com. One of our biggest engineering challenges is identifying the bad guys without impacting customer experience. We use the latest technologies like machine learning and calculations of complex variables / attributes of risk to detect these bad guys. You will work with other engineering teams at Amazon to develop novel solutions to improve the security of our customers' accounts and do so at Amazon scale. You will work with other engineering teams at Amazon to develop and strengthen security around customer accounts.
About the candidate... The ideal candidate for our team is passionate about creative solutions to our technical problems. You have technical curiosity, drive for results, but at the same time you embody ownership at the business level and contribute to product development.
Bachelors degree in Computer Science/related field or equivalent work experience
Experience with object oriented programming including Java, C++, C#, or C
Experience with distributed (multi-tiered) systems, algorithms, and relational databases
Experience in dealing with Machine Learning Models, optimization mathematics (linear programming, nonlinear optimization)
Deal well with ambiguous/undefined problems; ability to think abstractly
Strong, object-oriented design and coding skills (C/C++ and/or Java preferably on a UNIX or Linux platform)
Knowledge of Python or other scripting languages a plus
Graduate degree a plus
Strong written/spoken communication skills
Experience with system architecture/design
Experience with distributed systems operating in a scalable/high volume environment