Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&M, and Microsoft.
Responsibilities
Research, design, implement, train, deploy and monitor machine learning algorithms, either for batch prediction or real-time (on-line learning, clustering, supervised and semi-supervised learning, graph analysis, representation learning, AML systems, real-time anomaly detection based on time-series modeling).
Develop orchestrated pipelines for analytical purposes and machine learning training.
Contribute to ongoing automation efforts for experiments, training runs, validation runs and monitoring before, during and after deployment; collaborate with MLOps to improve machine learning tooling.
Collaborate closely with product managers and business stakeholders to understand requirements, define problems, and frame them as solvable machine learning tasks.
Explore and analyze large, complex datasets to identify patterns, insights, and opportunities for ML-driven solutions.
Define key performance metrics, design rigorous experiments (e.g., A/B tests), and perform statistical analysis to validate model performance and quantify business impact.
Requirements
5+ years of experience as a machine learning or data scientist.
Experience with the full machine learning model lifecycle in production flows.
Experience leveraging a big data framework to create the pipelines needed to feed the models with appropriate data.
Good understanding of software engineering practices as well as data engineering and MLOps principles.
Knowledge of data science and statistics and machine learning techniques, including a strong grounding in statistical inference, machine learning for prediction, and causal inference.
Conditions
Hands-on technical leadership role with influence over long-term technical direction while remaining close to implementation, experimentation, and production systems.