About the role
structured by ORIDescription Do you want to join an innovative team applying machine learning and advanced statistical techniques to protect Amazon customers and enable a trusted eCommerce experience? Are you excited about working with large-scale datasets and developing models that solve real-world fraud and risk challenges?
What you will do
- Apply machine learning and statistical techniques to build and improve risk management models
- Analyze large-scale historical data to identify risk patterns and emerging trends
- Develop, validate, and deploy innovative models under the guidance of senior scientists
- Experiment with emerging technologies, including GenAI/LLMs, to enhance automation and risk evaluation
- Collaborate closely with software engineers to implement models in real-time production systems
What they are looking for
- Experience programming in Java, C++, Python or related language
- Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse
- Master's degree in Engineering, Computer Science, Machine Learning, Operations Research, Statistics, or related fields
- Experience building machine learning models or developing algorithms for business application
Nice to have
- Experience implementing algorithms using both toolkits and self-developed code
- Have publications at top-tier peer-reviewed conferences or journals
Full posting text
Description
Do you want to join an innovative team applying machine learning and advanced statistical techniques to protect Amazon customers and enable a trusted eCommerce experience?
Are you excited about working with large-scale datasets and developing models that solve real-world fraud and risk challenges?
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 help develop scalable machine learning solutions that safeguard millions of transactions every day.
In this role, you will partner with senior scientists and engineers to translate business problems into data-driven solutions, build and evaluate models, and contribute to next-generation risk prevention systems, including applications of Generative AI and LLM technologies.
Key job responsibilities
Apply machine learning and statistical techniques to build and improve risk management models
Analyze large-scale historical data to identify risk patterns and emerging trends
Develop, validate, and deploy innovative models under the guidance of senior scientists
Experiment with emerging technologies, including GenAI/LLMs, to enhance automation and risk evaluation
Collaborate closely with software engineers to implement models in real-time production systems
Partner with operations and business teams to improve risk policies and operational efficiency
Build scalable, automated pipelines for data analysis, model training, and validation
Monitor model performance and provide clear reporting on key risk and business metrics
Research and prototype new modeling approaches to improve system performance
Basic Qualifications
Experience programming in Java, C++, Python or related language
Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse
Master's degree in Engineering, Computer Science, Machine Learning, Operations Research, Statistics, or related fields
Experience building machine learning models or developing algorithms for business application
Preferred Qualifications
Experience implementing algorithms using both toolkits and self-developed code
Have publications at top-tier peer-reviewed conferences or journals
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.
Employment type: Full-time
Industries: Research Services