Applied Scientist II, Buyer Risk Prevention (BRP)
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Job Location:
Monthly Salary:
Posted on:
21 hours ago
Vacancies:
1 Vacancy
Job Summary
Do you want to join an innovative team of scientists applying machine learning and advanced statistical techniques to protect Amazon customers and enable a trusted eCommerce experience
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 technologiesincluding Generative AI and LLMsto 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
- 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 in professional modelling/software development
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.
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 technologiesincluding Generative AI and LLMsto 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
- 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 in professional modelling/software development
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.
Required Experience:
IC
Key Skills
- Laboratory Experience
- Immunoassays
- Machine Learning
- Biochemistry
- Assays
- Research Experience
- Spectroscopy
- Research & Development
- cGMP
- Cell Culture
- Molecular Biology
- Data Analysis Skills
About Company
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