Ph3Applied Scientist II, AWS Fraud Prevention /h3 pAWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. /p pAre you passionate about solving complex problems and protecting one of the world’s largest cloud platforms? The AWS Fraud Prevention team is looking for an innovative Applied Scientist to help keep AWS a safe and trusted environment for millions of customers worldwide. /p pIn this role, you will design and deploy machine learning models to detect and mitigate fraud at scale. You will also have the opportunity to explore Generative AI (GenAI) techniques to uncover new fraud patterns and stay ahead of evolving threats. /p pAt AWS, we support hundreds of thousands of businesses, powering billions of transactions every day. Fraudsters are constantly innovating — and so are we. If you enjoy thinking like a fraudster, building resilient defenses, and making a real-world impact, we invite you to join us and help shape the future of secure cloud computing. /p h3Key job responsibilities /h3 ul liDesign, build, and deploy machine learning models to detect, prevent, and mitigate fraudulent activities across the AWS platform. /li liAnalyze large-scale behavioral, transactional, and historical datasets to uncover fraud patterns and emerging threats. /li liExplore and apply GenAI techniques, including large language models (LLMs), synthetic data generation, and adversarial simulations to enhance fraud detection capabilities. /li liCollaborate closely with engineering, product, and operations teams to translate business needs into scalable technical solutions. /li liExperiment, prototype, and iterate on new detection strategies, algorithms, and evaluation metrics. /li liContinuously monitor model performance and improve robustness against adversarial behaviors and evolving fraud tactics. /li liCommunicate findings and technical insights clearly and effectively to both technical and non-technical audiences. /li liContribute to the broader fraud prevention strategy, driving innovation and best practices across the organization. /li /ul h3About the team /h3 pDiverse Experiencesbr/AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. /p h3Why AWS? /h3 pAmazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. /p h3Inclusive Team Culture /h3 pHere at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and conferences, inspire us to never stop embracing our uniqueness. /p h3Mentorship Career Growth /h3 pWe’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. /p h3Work/Life Balance /h3 pWe value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. /p h3Basic Qualifications /h3 ul liExperience programming in Java, C++, Python or related language /li liExperience in state-of-the‑art deep learning models architecture design and deep learning training and optimization and model pruning /li liMaster's degree or above in computer science, machine learning, engineering, or related fields /li liExperience applying theoretical models in an applied environment /li /ul h3Preferred Qualifications /h3 ul liExperience in fraud detection, cybersecurity, anomaly detection, risk modeling, or adversarial machine learning. /li liHands‑on experience applying GenAI techniques such as synthetic data generation, adversarial simulation, or large language model (LLM) insights. /li liExperience designing and deploying machine learning models in production environments. /li liAbility to collaborate across multidisciplinary teams and clearly communicate technical concepts to non-technical audiences. /li /ul pOur inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. /p pbPosted: /b January 20, 2026 (Updated 2 days ago) /p pAmazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. /p /p #J-18808-Ljbffr