Do you want to lead the development of advanced machine learning systems that
protect millions of customers and power a trusted global eCommerce experience?
Are you passionate about modeling terabytes of data, solving highly ambiguous
fraud and risk challenges, and driving step-change improvements through
scientific innovation?
If so, the Amazon Buyer Risk Prevention (BRP) Machine Learning team may be the
right place for you.
We are seeking a Senior Applied Scientist to define and drive the scientific
direction of large-scale risk management systems that safeguard millions of
transactions every day. In this role, you will lead the design and deployment of
advanced machine learning solutions, influence cross-team technical strategy,
and leverage emerging technologies—including Generative AI and LLMs—to build
next-generation risk prevention platforms.
Key job responsibilities
Lead the end-to-end scientific strategy for large-scale fraud and risk modeling
initiatives
Define problem statements, success metrics, and long-term modeling roadmaps in
partnership with business and engineering leaders
Design, develop, and deploy highly scalable machine learning systems in
real-time production environments
Drive innovation using advanced ML, deep learning, and GenAI/LLM technologies to
automate and transform risk evaluation
Influence system architecture and partner with engineering teams to ensure
robust, scalable implementations
Establish best practices for experimentation, model validation, monitoring, and
lifecycle management
Mentor and raise the technical bar for junior scientists through reviews,
technical guidance, and thought leadership
Communicate complex scientific insights clearly to senior leadership and
cross-functional stakeholders
Identify emerging scientific trends and translate them into impactful production
solutions Basic Qualifications: - 3+ years of building machine learning models
for business application experience
- PhD, or Master's degree and