Applied Scientist, Seller Partner Trust and Store Integrity Science - Global Risk Intelligence and Prevention

Amazon Science

Seattle (WA)

On-site

USD 143,000 - 193,000

Full time

4 days ago
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Job summary

Amazon Science is seeking an Applied Scientist to lead AI-driven risk intelligence for the Global Selling Partner program. You will build predictive models to detect bad actors, fraught with fraudulent ownership transfers and identity manipulation, across the seller lifecycle.

You will own the scientific solution from risk quantification to decision optimization, collaborating with risk programs and engineering teams to deploy production-grade systems and measurable improvements.

Qualifications

  • PhD or Master’s with 4+ years in CS, CE, ML or related field.
  • Experience programming in Java, C++, Python.
  • Experience with ML and LLM fundamentals or recent development.
  • Knowledge of deep learning, ML and statistics.
  • Track record translating ambiguous business problems into ML solutions.

Responsibilities

  • Design and build predictive risk detection models using advanced AI techniques, including graph-based and network analysis, to identify bad actors.
  • Own the end-to-end scientific solution from risk quantification through decision optimization.
  • Develop interpretability and reasoning pipelines that provide explanations for model decisions.
  • Define detection strategies with risk programs across the seller lifecycle.
  • Partner with engineering to deploy models, define evaluation frameworks, and measure detection effectiveness.

Skills

ML fundamentals
Graph learning
Adversarial ML
Temporal data
Multi-modal data

Education

PhD or MSc with 4+ yrs CS/CE/ML

Tools

Java
C++
Python

Job description

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.

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.

USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually

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