Applied Scientist - Multiple Teams

Description

We are seeking an exceptional Applied Scientist, Global Selling Partner Risk Intelligence and Prevention, to lead the development and implementation of advanced AI solutions that will transform how we prevent bad actors from operating in our store and enable Selling Partners to start and grow their business without fear of disruption, so that customers and Selling Partners across the globe trust us and have confidence in the integrity of Amazon's store. This role will focus on building risk detection models leveraging state-of-the-art AI, including small language models, to identify compromised accounts, fraudulent ownership transfers, identity manipulation, and coordinated bad actor networks across the entire seller lifecycle, from registration through ongoing account management.

You will design, develop, and deploy scalable AI solutions to proactively detect and prevent marketplace abuse throughout the seller lifecycle. You will work with massive-scale, multi-modal datasets spanning behavioral patterns, transactional histories, and account relationship graphs to build predictive systems that stay ahead of evolving adversarial tactics.

Key job responsibilities
* Design and build predictive risk detection models using advanced AI techniques, including graph-based and network analysis methods, to proactively identify bad actors and prevent marketplace abuse at scale

* Own the end-to-end scientific solution from risk quantification through decision optimization, determining the appropriate actions to take across varying risk levels

* Develop interpretability and reasoning pipelines that provide transparent, actionable explanations for model decisions to support enforcement and seller experience

* Work with risk programs across the seller lifecycle to define detection strategies, translate operational investigation patterns into automated systems, and prioritize high-impact risk areas

* Partner with engineering teams to deploy models into production, define evaluation frameworks, and collaborate with operations and verification teams to measure and improve detection effectiveness

About the team
GRIP Science (Global Risk Intelligence & Prevention) is the core detection engine within TSI Science. We build and operate ML models that identify and block bad sellers across Amazon's 24 global marketplaces. Our models cover the full seller journey, from the moment they register through every action they take on the marketplace, and we score holistic risk across all active sellers.

Basic Qualifications

- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution, or experience in development in the last 3 years
- Knowledge of deep learning, machine learning and statistics
- Track record of translating ambiguous business problems into well-defined ML solutions

Preferred Qualifications

- Experience in professional software development
- PhD
- Experience with adversarial ML, fraud detection, or abuse prevention systems
- Familiarity with graph-based learning methods for detecting coordinated networks
- Experience modeling temporal and sequential data (e.g., account behavior over time, event sequences)
- Experience building models that operate on multi-modal data (text, structured, behavioral signals)

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.