$ cat jobs/machine-learning-scientist-i-protect-adyen-13d144882a27.json
Machine Learning Scientist I - Protect
This is Adyen Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&M, and Microsoft - making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition. For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster. Machine Learning Scientist I - Protect Adyen is looking for a Machine Learning Scientist I to join our Protect team in Amsterdam. As part of Protect, you will help us build the next generation of real-time fraud prevention systems. Our team owns the machine learning models embedded directly into Adyen’s core payment flow, scoring over 100 million transactions daily to stop evolving fraud in real time. In this role, you will work alongside experienced Machine Learning Scientists, Engineers, and Data Analysts to build, train, deploy, and monitor scalable models that secure global online payments. What You Will Do: Develop & Train ML Models: Assist in researching, training, and evaluating machine learning models used for real-time risk assessment, anomaly detection, behavioural prediction, and fraud prevention. Pipeline Development: Help build and maintain batch and streaming data pipelines to feed online feature stores and analytical workflows. Model Lifecycle & Monitoring: Support the continuous improvement of our models by contributing to ongoing automated experiments, validation runs, and real-time performance monitoring. Cross-Functional Collaboration: Partner closely with peers in engineering, product, and analytics to translate business requirements into actionable machine learning tasks and merchant-facing risk tools. Data Exploration: A
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