Applied Scientist: Payments Fraud Prevention & GenAI

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

Benefits offered by this job

Health insurance

401(k) matching

RSUs

Parental leave

Job summary

Amazon Science in Seattle is seeking an Applied Scientist to design, build, and deploy machine learning models that detect and prevent fraud across the AWS platform.

You will work with massive datasets, develop new detection strategies, and apply GenAI techniques to strengthen fraud defenses while collaborating with engineering, product, and operations teams to translate business needs into scalable solutions.

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 algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

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 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.

Skills

PhD or MS+4+ years

Model development experience

Java/C++/Python

Deep learning architectures

Algorithms & data structures

Education

PhD or MS in CS/CE/ML

Tools

Java

C++

Python

Job description

Amazon Science in Seattle is seeking an Applied Scientist to design, build, and deploy machine learning models that detect and prevent fraud across the AWS platform.

You will work with massive datasets, develop new detection strategies, and apply GenAI techniques to strengthen fraud defenses while collaborating with engineering, product, and operations teams to translate business needs into scalable solutions.