Applied Scientist I, Buyer Risk Prevention

04 ott - Italia
Amazon

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? Si candidi rapidamente per massimizzare le sue possibilità di essere considerato/a per un colloquio. 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.
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
Research and prototype new modeling approaches to improve system performance
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
Experience implementing algorithms using both toolkits and self-developed code
Our inclusive culture empowers Amazonians to deliver the best results fo

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