Applied Scientist: Cloud Payments & Fraud Detection

Amazon; Seattle (WA); On-site; USD 143,000 - 193,000; Full time

Job summary

Amazon in Seattle, WA is seeking an Applied Scientist for AWS Payments and Fraud Prevention. You will design, build, and deploy ML models to detect and mitigate fraudulent activity across AWS, working with massive datasets and exploring GenAI techniques to strengthen defenses.

Collaborating with engineering, product, and operations teams, you will prototype new strategies, monitor performance, and communicate findings to diverse audiences.

Qualifications

• PhD, or Master's with 4+ years CS/CE/ML experience.
• 3+ years building models for business applications.
• Proficient in Java, C++, Python.
• Experience with state-of-the-art DL models and optimization.
• Familiarity with algorithms, data structures, and HPC.

Responsibilities

• Design, build, and deploy ML models to detect fraud.
• Analyze large-scale behavioral, transactional datasets.
• Explore GenAI techniques to enhance detection.
• Collaborate with engineering, product, operations teams.
• Prototype and iterate on detection strategies.
• Monitor model performance and robustness.
• Communicate insights to technical and non-technical audiences.
• Contribute to fraud prevention strategy across the org.

Skills

ML model development

Programming: Java/C++/Python

Deep learning

Algorithms & data structures

Distributed computing

Education

PhD

Master's degree

Tools

GenAI

Analytics tools

Database

Cloud storage

Job description

Amazon in Seattle, WA is seeking an Applied Scientist for AWS Payments and Fraud Prevention. You will design, build, and deploy ML models to detect and mitigate fraudulent activity across AWS, working with massive datasets and exploring GenAI techniques to strengthen defenses.

Collaborating with engineering, product, and operations teams, you will prototype new strategies, monitor performance, and communicate findings to diverse audiences.