Applied Scientist, Denied Party Screening (DPS), AWS Compliance & Security Assurance
Core
Build automatic mechanisms using ML/AI to detect and prevent prohibited transactions with denied entities, screening over a billion events daily.
Role type
Applied Scientist (ML/AI)
Builds
ML/AI-powered detection and resolution systems for denied party screening
Domain
Cybersecurity / Financial Compliance
Deliverable
production ML models
Required skills
Machine learning model development, algorithm design, Java, C++, Python, statistical analysis, deep learning training and optimization
Preferred skills
Generative deep learning models (CNNs, GANs, VAEs, NF), state-of-the-art deep learning architecture design, model pruning
Technologies
Java, C++, Python, CNNs, GANs, VAEs, NF
Responsibilities
Drive research and development of novel ML/AI models, prototype and iterate on solutions, analyze complex datasets, present research findings to leadership, mentor junior scientists
Seniority
Mid-Senior, hands-on IC