AmazonPosted 1d ago

Applied Scientist, AWS Payments and Fraud Prevention

Applied Scientist, AWS Payments and Fraud Prevention at Amazon scores 90 out of 100 on AI centrality, which makes it a Level 4 role on this board.

US, WA, Seattleseniorfull-time$143k-$193k

AI in this role

Applied Scientist designing and deploying machine learning and GenAI models for payment fraud detection on AWS.

pythonllms

Are you passionate about solving complex problems and protecting one of the world’s largest cloud platforms? The AWS Payments and Fraud Prevention team is looking for an innovative Applied Scientist to help keep AWS a safe and trusted environment for millions of customers worldwide.
In this role, you will design, build, and deploy machine learning models that detect, prevent, and mitigate fraudulent activity across the AWS ecosystem. You will work with massive, real-world datasets, develop new detection strategies, and apply advanced and practical technologies to tackle ever-evolving threats. You will also explore Generative AI (GenAI) techniques to uncover new fraud patterns and strengthen our fraud defenses.
At 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.

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.
* Collaborate closely with engineering, product, and operations teams to translate business needs into scalable technical solutions.
* 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.

About the team
AWS Payments and Fraud Prevent is responsible for detecting & mitigating AWS account risks. You’ll be part of a team of Scientists, Analysts, and Technical & non-Technical Program Managers. The team’s goal is to identify and neutralize fraudsters from unauthorized access to legitimate AWS customers accounts.

We have a formal mentor search application that lets you find a mentor that works best for you. Your manager can also help you find a mentor or two, because two is better than one. In addition to formal mentors, we work and train together so that we are always learning from one another, and we celebrate and support the career progression of our team members.

Basic qualifications

- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- 3+ years of building models for business application experience
- 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
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

Preferred qualifications

- Experience with any combination of the following: application security frameworks, identity and access controls, incident response, mobile security, cloud computing and security, AI security, threat intelligence, and penetration testing
- Experience working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage
- Experience communicating technical concepts to non-technical audiences, or experience in similar environments

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our 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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually

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PythonLlms

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What's a project where you used Python hands-on?
Walk me through how you've used Llms in your day-to-day work.
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Tell me about a time a model underperformed in production. How did you find out, and what did you change?

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Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
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