Amazon Data Scientist SMGS Security Escalations 

United States, Kansas 

344208705

This role with partner with the existing Security Experts to validate that security controls are enabled throughout the lifecycle of traditional Machine Learning and Generative AI phases of model development. The security controls will be defined from the early experimentation phases to model fine-tuning to model deployment and ongoing operational governance.Key job responsibilities• Lead the development of security guidance on the use of AI/ML, particularly generative AI • Design, develop, and evaluate innovative ML models to solve diverse challenges and opportunities across industries. • Collaborate with security experts to validate and recommend security controls applicable for all phases of AI/ML/Gen AI development lifecycle • Design, build, test, and help deploy ML and generative AI solutions that have measurable business and customer impact in security. • Interact with internal and external customers to understand their business problems and help them in implementation of their generative AI and ML solutions • Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder • Create detailed security documentation of solutions using reference architectures and implementation/configuration guidance • Collaborate with AI/ML peers to research, design, develop, and evaluate cutting-edge generative AI algorithms to address real-world challenges • Provide customer and market feedback to Service and Engineering teams to help define product direction • Work with a cross section of AI experts to develop solutions that will be piloted with customers for their production workloadsA day in the life

- 1+ years of data scientist experience
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 1+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Experience applying theoretical models in an applied environment