Are you passionate about building machine learning systems that protect one the world's largest cloud platform? The AWS Payments & Fraud Prevention (P&FP) Science team is looking for a driven Applied Scientist to help safeguard AWS and its millions of customers from evolving fraud threats.

In this role, you will design, build, and deploy end-to-end machine learning models that detect and prevent fraudulent activity. You will work with massive, real-world datasets across the AWS payments, signup and usage ecosystem, develop new detection strategies, and take models from concept to production. You will also apply Generative AI (GenAI) techniques to enhance fraud signal discovery and strengthen our detection capabilities.

At AWS, we process billions of transactions every day for hundreds of thousands of businesses worldwide. Fraud patterns shift constantly and our defenses must stay ahead. If you enjoy owning problems end-to-end, shipping models that make real-time decisions at scale, and making a direct impact on customer trust and financial protection, we invite you to join us and help shape the future of fraud prevention at AWS.

Key job 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.

A day in the life

You will have the opportunity to enhance our existing models and develop new ones that have a direct impact on the business from reducing financial losses to protecting customer accounts in real time. You will own your models end-to-end, from sourcing data and building features through evaluation and productionalization, and you will be expected to move quickly as fraud threats evolve.

As part of this role, you will also support core fraud operations reviewing model outputs, tuning detection thresholds, and ensuring our mechanisms are performing as expected in production. This operational closeness to the data and to real fraud cases is what gives our scientists a unique edge: you will develop a deep, practical understanding of how fraud actually works, which directly sharpens the models and strategies you build. It is this combination of science and operational insight that makes our team's work so impactful.

Your role will also allow you to leverage your customer-obsession skills by thoughtfully considering the user experience and ensuring it is not adversely affected by the mechanisms you design. You will explore new techniques, including Generative AI, to stay ahead of increasingly sophisticated adversaries.

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

- 5+ years of designing experiments and statistical analysis of results experience

- Experience programming in Java, C++, Python or related language

- 3+ years of practical work applying ML to solve complex problems for large-scale applications experience

- Experience with R, Python, Weka, SAS, Matlab or other statistical/machine learning software

- Experience in scripting for automation (e.g. Python) and advanced SQL skills.

- Experience working in a large team or fast-paced corporate environment

- PhD or equivalent Master's degree in Machine Learning, Artificial Intelligence, Mathematics, Statistics, Computer Science, Operations Research or in another highly quantitative field

- Ability to develop and deploy (in partnership with engineers) Machine Learning models that power specific applications

- Skilled in various Statistical and traditional Machine Learning methods such as tree-based models

- Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts

PREFERRED QUALIFICATIONS

- Experience using Unix/Linux

- Experience in professional software development

- Experience with neural deep learning methods and machine learning

- Knowledge of AWS Infrastructure

- Knowledge of AWS services including compute, storage, networking, security, databases, machine learning, and serverless technologies

- 4+ years of applied ML experience in a quantitative filed

- Predictive Analytics

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, NY, New York - 172,400.00 - 223,400.00 USD annually