Sr. Applied Scientist, WWOS Tech
Core
Build ML models to detect theft, fraud, and organized crime rings within Amazon's global supply chain and operations.
Role type
Sr. Applied Scientist (Fraud Detection & Supply Chain Security)
Builds
Intelligent, self-learning systems for fraud detection and theft automation
Domain
E-commerce / Supply Chain / Fraud Detection
Deliverable
production ML models
Required skills
Machine learning model development, neural deep learning methods, data-driven decision making, strategic problem solving, end-to-end evaluation of system gaps, stakeholder presentation, ML model integration
Preferred skills
Large scale distributed systems modeling, advanced modeling tools (R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy)
Technologies
Java, C++, Python, R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy, Hadoop, Spark
Responsibilities
Own KPIs measuring theft/fraud management performance, detect and automate theft/fraud methods, detect organized crime rings and bad actor clusters, evaluate operational defects and scaling challenges, contribute to fraud management strategies, present learnings to leadership, integrate ML detection models
Seniority
Senior, hands-on IC with strategic autonomy
