Payments & Fraud AI Scientist - End-to-End ML

Amazon Inc.; Seattle, Northern (WA, KY); Hybrid; USD 172,000 - 223,000; Full time

Job summary

Amazon Inc. is seeking an Applied Scientist for AWS Payments & Fraud Prevention to build end‑to‑end ML models and rules that detect and prevent fraudulent activity across the AWS ecosystem.

You will source and analyze large datasets, apply statistical methods, and deploy production‑ready models with product and engineering teams. You will explore GenAI techniques, including LLMs and synthetic data generation, and continuously monitor model performance to stay ahead of evolving fraud threats.

Qualifications

• PhD, or Master's with 4+ years in CS/ML or related field.
• 3+ years building models for business use.
• 5+ years designing experiments and statistical analysis.
• Proficient in Java, C++, Python or similar.
• 3+ years applying ML to large-scale problems.
• Experience with R, SAS, Matlab or similar ML software.
• Strong SQL scripting skills.
• Experience working in large teams or fast-paced environments.
• PhD or equivalent in a quantitative field.
• Ability to deploy ML models with engineers.

Responsibilities

• Design, build, and deploy end-to-end machine learning models and rules to detect, prevent, and mitigate fraudulent activities across the AWS payment and usage ecosystem.
• Source, extract, and analyze large-scale behavioral, transactional, and historical datasets to uncover fraud patterns and emerging threats.
• Apply hands-on expertise in statistical modeling, traditional machine learning, and analytics to identify and isolate issues across the fraud landscape.
• Explore and apply GenAI techniques, including large language models (LLMs) and synthetic data generation, to enhance fraud detection capabilities.
• Own the full model lifecycle — from data extraction and feature engineering through evaluation, productionalization, and deployment.
• Continuously monitor model and rule performance and improve robustness against adversarial behaviors and evolving fraud tactics.
• Experiment, prototype, and iterate on new detection strategies, algorithms, and evaluation metrics with a focus on rapid time-to-production.
• Collaborate closely with engineering, product, and operations teams to translate business needs into scalable technical solutions.
• Communicate findings and technical insights clearly and effectively to both technical and non-technical stakeholders at all levels.
• Contribute to the broader fraud prevention strategy, driving innovation and best practices across the organization.

Skills

ML Modeling

Fraud Detection

GenAI

Java

Python

SQL

Communication

Experimentation

Education

PhD in a quantitative field

Master's in CS/CE/ML or related

Tools

Java

Python

R

SAS

Matlab

SQL

Job description

Amazon Inc. is seeking an Applied Scientist for AWS Payments & Fraud Prevention to build end‑to‑end ML models and rules that detect and prevent fraudulent activity across the AWS ecosystem.

You will source and analyze large datasets, apply statistical methods, and deploy production‑ready models with product and engineering teams. You will explore GenAI techniques, including LLMs and synthetic data generation, and continuously monitor model performance to stay ahead of evolving fraud threats.