Sr. Applied Scientist, AppStar Data Analytics & Engineering
Core
Invent and build ML-driven systems to identify, prioritize, and mitigate application security risk at scale for Amazon.
Role type
Senior Applied Scientist (Security)
Builds
Risk-scoring models, graph-based systems, and analytics platforms for application security
Domain
Cybersecurity / Machine Learning
Deliverable
production ML models
Required skills
Machine learning model development, neural deep learning, Java, C++, Python, graph-based modeling, large-scale dataset analysis
Preferred skills
R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy, Hadoop, distributed systems
Technologies
AWS (S3, Glue, SageMaker, Neptune), Java, C++, Python, R, Spark, Tensorflow
Responsibilities
Design and deploy ML models for security prioritization and risk assessment, frame ambiguous security problems into scientific challenges, architect production ML pipelines on AWS, develop graph-based models for security relationships, drive scientific agenda and experiments, partner with engineers to translate model outputs, establish scientific rigor and best practices
Seniority
Senior, hands-on IC