About this role
The WWOS Tech team at Amazon is seeking a Sr. Applied Scientist to develop intelligent, self-learning systems to detect theft, fraud, and organized crime across global supply chain operations. This role involves owning business challenges, building ML models, and using data-driven insights to influence organizational change and maximize cost savings related to inventory losses. Responsibilities include managing KPIs for fraud performance, automating theft detection, identifying organized crime rings, evaluating operational defects, and integrating ML models into software applications. Candidates must be comfortable working in an ambiguous environment and presenting findings to leadership. Basic Qualifications: 3+ years of experience building machine learning models for business applications; PhD, or Master's degree with 6+ years of applied research experience; proficiency in Java, C++, or Python; and experience with neural deep learning methods. Preferred Qualifications: Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, and scipy; and experience with large-scale distributed systems like Hadoop and Spark.