Applied Scientist II, Identity Security & Abuse Prevention

Amazons Identity Security & Abuse Prevention (ISAP) team is seeking an Applied Scientist to join our team. We discover analyze and quantify security risks across Amazons identity and authentication landscape transforming complex behavioral patterns into actionable intelligence that empowers teams to proactively defend against abuse and unauthorized access.

In this role you will design build and own machine learning systems that detect abuse patterns classify threats and automate enforcement across sensitive datasets spanning multiple Amazon verticals. You will independently frame ambiguous detection problems develop novel approaches to abuse prevention and deploy production ML systems that directly protect Amazon customers and sellers at scale. You will work at the intersection of applied science and security operations translating complex abuse vectors into scalable detection capabilities.

This is a high-ownership role where your models and systems run autonomously in production making real-time decisions that prevent fraud and abuse. You will own both existing detection capabilities (improving precision recall and coverage of current models) and greenfield science (designing and deploying new detection systems for emerging threat vectors). You will lead experimental design extend or invent methodologies for your domain mentor junior scientists and contribute to the teams scientific roadmap. You will partner with investigators security engineers and data engineers to build end-to-end detection and enforcement pipelines and you will leverage GenAI LLMs and AI-agent architectures to advance our abuse prevention capabilities.

Key job responsibilities
- Design develop and deploy production ML systems for abuse pattern detection anomaly detection threat classification and automated enforcement across multiple Amazon verticals

- Independently frame ambiguous security and abuse problems into well-defined scientific questions propose detection approaches and drive them from hypothesis through production deployment

- Own and improve existing detection models end-to-end: monitor for drift diagnose degradation retrain and extend coverage as abuse patterns evolve

- Build and maintain graph-based entity analysis identity resolution and modus operandi classification systems that link bad actors across accounts devices and behavioral signals

- Design and execute rigorous experiments (A/B testing offline evaluation statistical validation) to measure model performance and quantify business impact

- Architect and deploy GenAI and LLM-based solutions for investigation automation case classification and intelligent knowledge retrieval


- Contribute to the teams scientific roadmap by identifying high-value detection opportunities proposing new approaches and driving prioritization of science investments

- Publish research findings in internal Amazon papers and at external peer-reviewed conferences; contribute to the broader scientific community

- Partner with investigators security engineers and data engineers to understand abuse patterns translate operational insights into model features and ensure detection systems drive real enforcement actions

A day in the life
Your morning might start with reviewing model performance dashboards for a classifier you deployed last month noticing a subtle precision drop that suggests adversarial adaptation. You diagnose the drift propose a feature addition to counter the new pattern and kick off a retraining job. Mid-morning you lead a design review on a new graph-based detection approach you developed to identify organized abuse rings operating across multiple verticals. After lunch an investigator shares a newly identified modus operandi and you explore the data to determine if the pattern is learnable at scale sketching an experimental design. Late afternoon you pair with a junior scientist on their anomaly detection model helping them refine their evaluation methodology and avoid a common statistical pitfall. You close the day by drafting a section of a research paper on your entity resolution approach preparing it for internal peer review.

About the team
The ISAP SafeGuard team mixes long-term high-impact projects with near-term innovative solutions to prevent abuse across Amazon. We balance Bias for Action Dive Deep Invent and Simplify and Customer Trust daily. Our team embraces new approaches technology and innovation while ensuring our solutions are scalable accurate and drive action. We work with some of the most sensitive data at Amazon which requires thoughtful engineering strict access controls and a strong sense of responsibility. If you are energized by building ML systems that directly protect customers and sellers from bad actors at scale this is the team for you.

Diverse Experiences
Amazon Security values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description we encourage candidates to apply. If your career is just starting hasnt followed a traditional path or includes alternative experiences dont let it stop you from applying.

Why Amazon Security
At Amazon security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazons products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud devices retail entertainment healthcare operations and physical stores.

Inclusive Team Culture
In Amazon Security its in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas perspectives and voices.

Training & Career Growth
Were continuously raising our performance bar as we strive to become Earths Best Employer. Thats why youll find endless knowledge-sharing training and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home theres nothing we cant achieve.

- 3 years of building models for business application experience
- PhD or Masters degree and 4 years of CS CE ML or related field experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- 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 using Unix/Linux
- Experience in professional software development
- Experience with large scale distributed systems such as Hadoop Spark etc.
- Experience managing confidential and sensitive employee information and adherence to strict confidentiality standards
- Experience in fraud investigation abuse cyber-crimes or equivalent
- Experience in one or more of: anomaly detection classification graph neural networks temporal modeling or causal inference
- Familiarity with LLM fine-tuning reward modeling or feedback signal design
- Familiarity with RAG systems knowledge graphs or memory-augmented architectures

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 for more information. If the country/region youre applying in isnt 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 WA Seattle - 142800.00 - 193200.00 USD annually