Amazon Applied Scientist AWS Fraud Prevention 

United States, Washington, Seattle 

178977120

Key job responsibilities
* Design, build, and deploy machine learning models to detect, prevent, and mitigate fraudulent activities across the AWS platform.
* Analyze large-scale behavioral, transactional, and historical datasets to uncover fraud patterns and emerging threats.
* Explore and apply GenAI techniques, including large language models (LLMs), synthetic data generation, and adversarial simulations to enhance fraud detection capabilities.* Experiment, prototype, and iterate on new detection strategies, algorithms, and evaluation metrics.
* Continuously monitor model performance and improve robustness against adversarial behaviors and evolving fraud tactics.
* Communicate findings and technical insights clearly and effectively to both technical and non-technical audiences.
* Contribute to the broader fraud prevention strategy, driving innovation and best practices across the organization.

- Experience programming in Java, C++, Python or related language
- Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning
- Master's degree or above in computer science, mathematics, statistics, machine learning or equivalent quantitative field
- Experience applying theoretical models in an applied environment