Applied Scientist I, Buyer Risk Prevention (BRP)
Core
Develop scalable machine learning solutions to protect customers and enable trusted eCommerce experiences by solving real-world fraud and risk challenges.
Role type
Applied Scientist (Machine Learning)
Builds
Next-generation risk prevention systems, automated pipelines, and real-time production models
Domain
eCommerce, Fraud Detection, Risk Management
Deliverable
production ML models
Required skills
Machine learning, statistical techniques, Java, C++, Python, SQL, RDBMS, algorithm development, Generative AI, LLM technologies
Preferred skills
Algorithm implementation using toolkits and self-developed code, publications at top-tier peer-reviewed conferences or journals
Technologies
Generative AI, LLMs, Oracle, Data Warehouse
Responsibilities
Build and improve risk management models, analyze large-scale historical data to identify risk patterns, develop and validate innovative models, experiment with GenAI/LLMs, collaborate with engineers to implement models in real-time systems, build scalable automated pipelines, monitor model performance and report metrics, research and prototype new modeling approaches
Seniority
Individual Contributor (IC)
