104 Statistical Modeling Jobs in Bangalore / Bengaluru

Amazon. coms Risk Management Team has a worldwide reputation as the #1 in eCommerce Fraud Prevention. Trust and Safety of our customers comes first. Always. We thrive on maintaining the highest bar of customer experience while we maintain those tenets. Do you want to join a team that uses cutting edge technology including machine learning and statistical modeling techniques, cloud computing services and highly available and scalable distributed systems that supports hundreds of millions of transactions across the globe?

The Unified Risk Evaluation System team owns the charter of evaluating bad actor risk of all kinds (Buyer, Seller, Vendor) across entities such as Orders, Purchases, Signins and any event that will be useful to evaluate risky behavior. We process every single order and purchase in real time, totaling to more than 50 Billion evaluations in a year saving Billions of dollars that would otherwise be lost to bad actors. We build self-service capabilities to experiment new machine learning models and make it easy to onboard and manage 100s of risk use cases all over the world. We are the gate keepers of customer trust by preventing bad actors from doing damage to good customers or scamming Amazon. The problems we solve will challenge the best in terms of scale, ingenuity of bad actors and the cost of making risk decisions through bold goals we take such as automate 100% of risk decisions or reduce fraud and Abuse by 50% year over year.

Come join the best in class team of engineers, who are owners, and inventors. We are at the intersection of Machine Learning and Security, while delivering customer impact at amazon scale. Interact with ML scientists on a daily basis, and build the platform to beat to keep the bad guys out.
- 8+ years of non-internship professional software development experience
- 8+ years of programming with at least one software programming language experience
- 8+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience as a mentor, tech lead or leading an engineering team