Machine Learning Scientist

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

The Insights team is at the core of Adyen’s platform, providing the world’s largest merchants with the data and analytics they need to optimize their payment performance. Within this, our Proactive Diagnostics initiative acts as a proactive guard for merchant revenue, closing the loop between detecting an anomaly and providing a clear path to rectification.

We operate at the intersection of Big Data and actionable intelligence. By leveraging Adyen’s global payment flow, we apply advanced statistical models and Causal Inference to not only detect performance drops but to explain the why behind them. We are looking for a Machine Learning Engineer to help us architect the next generation of our diagnostic engine.

In this role, you will:

• Build – Design and scale production-ready ML models to identify anomalies across millions of traffic permutations. You will own the end-to-end lifecycle, from feature engineering within our Big Data ecosystem (Spark/SparkStreaming) to building the internal infrastructure—such as our FastAPI-based labeling service on Kubernetes—needed to generate high-quality ground truth for supervised learning.
• Discover – Move beyond simple detection to build automated root-cause analysis. You will develop logic that translates complex statistical signals into actionable recommendations, helping merchants understand exactly how to optimize their setup.
• Scale – Transition our diagnostic capabilities from daily reporting to near-real-time velocity. You will build the observability layer to track model drift and integrity, ensuring our signals remain the "Gold Standard" for the industry.
• Collaborate – Work at the heart of a product-driven team. You will sit close to our users, gathering continuous feedback to ensure our technical solutions solve real-world business friction and drive product adoption.

Who You Are:

• You have 4+ years of experience as a Machine Learning Engineer or Data Scientist (Anomaly Detection, Time-Series, or Signal Processing).
• You have an Engineering-First mindset. You treat ML code like production code and are comfortable managing your own deployments and infrastructure.
• You are proficient in Python and Big Data frameworks (PySpark, Airflow, Hadoop, Kafka).
• Experience with SparkStreaming/Flink, Docker and Kubernetes is a plus.
• You have a strong interest in Causal Inference - you want to prove why something happened, not just that it happened.
• You are a pragmatic problem solver. You prioritize business impact and reliability over model complexity, choosing the right tool for the job to ship solutions that work today.
• You are proactively taking the lead in projects, from ideation to deployment. You have experience working with a wide range of stakeholders and can clearly communicate complex outcomes to a wide range of audiences.
• You can confidently work in a product team with demanding stakeholders, are able to communicate effectively and have the ability to drive the team’s roadmap, alongside the product and engineering leadership of the team.

This role is based out of our Amsterdam office. We are an office-first company and value in-person collaboration; we do not offer remote-only roles.