Applied Scientist - Fraud Risk & ML

Amazon; San Diego (CA); On-site; USD 143,000 - 193,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Job summary

Amazon is seeking a Machine Learning Scientist for the Buyer Risk Prevention team in San Diego to build advanced models that prevent eCommerce fraud and improve customer experience. You will work on end-to-end risk metrics, leverage terabytes of data, and deliver scalable solutions with strong collaboration across software, data engineering, and operations teams.

The role requires a PhD or MS with several years of ML experience, fluency in Python/Java/C++, and a track record of deploying models

Qualifications

• 3+ years building models for business applications.
• PhD or Master’s with 4+ years in CS/CE/ML or related field.
• Proficiency in Java, C++, Python or related languages.

Responsibilities

• Use ML and statistical techniques to create scalable risk management systems.
• Analyze large historical data to identify risk patterns and trends.
• Design, develop and evaluate innovative models for risk management.
• Collaborate with software engineering to implement real-time model solutions.
• Support operations with scalable analytics and automated processes.
• Provide regular management reporting on risk and activity.
• Research novel ML approaches and validate new methods.

Skills

Machine learning

Model building

Programming languages

Education

PhD or MS + 4 years CS/CE/ML

Tools

Python

Java

C++

Job description

Amazon is seeking a Machine Learning Scientist for the Buyer Risk Prevention team in San Diego to build advanced models that prevent eCommerce fraud and improve customer experience. You will work on end-to-end risk metrics, leverage terabytes of data, and deliver scalable solutions with strong collaboration across software, data engineering, and operations teams.

The role requires a PhD or MS with several years of ML experience, fluency in Python/Java/C++, and a track record of deploying models