AmazonApplied Scientist II, Buyer Risk Prevention (BRP)
AI in this role
Design and deploy machine learning and generative AI models to detect fraud and secure eCommerce transactions for Amazon.
Are you excited about modeling terabytes of data and building state-of-the-art algorithms to solve complex, real-world fraud and risk challenges?
Do you enjoy owning end-to-end machine learning problems, directly influencing customer experience and company profitability, while collaborating in a diverse, high-performing team?
If so, the Amazon Buyer Risk Prevention (BRP) Machine Learning team may be the right fit for you. We are seeking an Applied Scientist to design, develop, and deploy advanced algorithmic systems that safeguard millions of transactions every day.
In this role, you will independently drive model development from problem formulation to production deployment, build scalable ML solutions, and leverage emerging technologies—including Generative AI and LLMs—to enhance fraud detection and next-generation risk prevention systems.
Key job responsibilities
Own end-to-end development of machine learning models for large-scale risk management systems
Analyze large volumes of historical and real-time data to identify fraud patterns and emerging risk trends
Design, develop, validate, and deploy innovative models to production environments
Apply GenAI/LLM technologies to automate risk evaluation and improve operational efficiency
Collaborate closely with software engineering teams to implement scalable, real-time model solutions
Partner with operations and business stakeholders to translate risk insights into measurable impact
Establish scalable and automated processes for data analysis, model experimentation, validation, and monitoring
Track model performance and business metrics; communicate insights clearly to technical and non-technical stakeholders
Research and implement novel machine learning and statistical methodologies
Basic qualifications
- 3+ years of building models for business application experience
- PhD, or Master's degree
- 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
Preferred qualifications
- Experience using Unix/Linux
- Experience in professional software development
- Experience in software development and delivery
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.
How we rate this
Applied Scientist II, Buyer Risk Prevention (BRP) at Amazon rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where fraud detection was part of your work. What did you do?
- Tell me about a project where risk management was part of your work. What did you do?
- Tell me about a project where algorithms was part of your work. What did you do?
- Tell me about a project where generative ai was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Machine Learning, Fraud Detection, Risk Management, Algorithms, and Generative AI. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
Want an expert to read your CV for this job?
Free. Send your CV and the role you want next. We reply by email within 2 to 4 business days.
Get a free CV reviewGet new applied scientist jobs (Builds AI ●●●●) by email
One email a week with the new applied scientist jobs (Builds AI ●●●●), each rated for how much AI is in the work. No recruiter spam, unsubscribe in one click.
Free. One email a week. Unsubscribe in one click.
Similar roles
Research roles that build AI, at other companies.
What kind of AI work fits you?
Answer 12 practical questions in about three minutes. Get a simple profile, the work it points to, and live roles to explore next.
Find my next step