Applied Scientist: Fraud Risk ML Systems

Amazon Inc.; Austin (TX); Hybrid; USD 143,000 - 193,000; Full time

Benefits offered by this job

Health insurance

RSUs

401(k) matching

Paid time off

Job summary

Amazon.com Services LLC is seeking a highly skilled Machine Learning Scientist to join the Buyer Risk Prevention (BRP) team. The role focuses on building scalable risk management models using ML and GenAI, analyzing terabytes of historical data to identify risk trends, and delivering end-to-end model implementations in collaboration with software and operations teams.

Qualifications include 3+ years of model-building experience or a PhD with relevant experience, plus proficiency in

Qualifications

• 3+ years building models for business applications
• PhD or Master’s with 4+ years in CS/CE/ML related field
• Experience in Java, C++, Python or related language
• Experience in algorithms/data structures, data mining, parallel and distributed computing

Responsibilities

• Use machine learning and GenAI techniques to create scalable risk management systems
• Learning and understanding large amounts of Amazon’s historical business data for specific instances of risk or broader risk trends
• Design, development and evaluation of innovative models for risk management
• Collaborating with software engineering teams to drive real-time model implementations and new features
• Collaborating with operations staff to optimize risk management operations
• Establishing scalable, automated processes for large-scale data analyses, model development, validation and implementation
• Tracking general business activity and providing regular management reporting
• Research and implement novel machine learning and statistical approaches

Skills

Machine Learning

Statistics

Java

Python

C++

Education

PhD in CS/ML/Statistics

Masters in CS/ML related field

Tools

SQL

Spark

Python

Perl

Job description

Amazon.com Services LLC is seeking a highly skilled Machine Learning Scientist to join the Buyer Risk Prevention (BRP) team. The role focuses on building scalable risk management models using ML and GenAI, analyzing terabytes of historical data to identify risk trends, and delivering end-to-end model implementations in collaboration with software and operations teams.

Qualifications include 3+ years of model-building experience or a PhD with relevant experience, plus proficiency in