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Senior Machine Learning Scientist

Posted 5 Jul 2026
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Work experience
5 to 10 years
Full-time / part-time
Full-time
Job function
Degree level
Required language
English (Fluent)

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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.

Adyen is looking for a Senior Machine Learning Scientist to join the team in Amsterdam, sitting at the cornerstone of algorithms, mathematics, and engineering, and solving problems by designing and implementing production-ready machine learning solutions. You will be responsible for building, developing and deploying algorithms that power data products at Adyen.

Teams Currently Hiring:

  • Optimise
  • Protect
  • Regulatory Reporting Technology

In this role, you will:

  • Research, design, implement, train, deploy and monitor machine learning algorithms, either for batch prediction or real-time. Examples include: on-line learning algorithms to pick the best optimization decision in a changing environment, clustering algorithms to group customers/shoppers, supervised and semi-supervised learning methods for inference on risk patterns or graph analysis, representation learning for behavior prediction and monitoring, Anti-Money Laundering (AML) systems and 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. Furthermore, 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;

Who you are:

  • You have 5+ years of experience as a machine learning or data scientist;
  • You have experience with the full machine learning model lifecycle in production flows;
  • You have experience leveraging a big data framework to create the pipelines needed to feed the models with appropriate data;
  • You have a good understanding of software engineering practices as well as data engineering and MLOps principles;
  • You have knowledge of data science, statistics, and machine learning techniques. These include a strong grounding in statistical inference, machine learning for prediction, and causal inference - Deep Learning experience is a plus;
  • You have strong familiarity with the standard data science toolkit, such as (py)spark, (Trino) SQL, Tensorflow, PyTorch, XGBoost/LightGBM, Pandas, MLFlow or similar MLOps frameworks, and Airflow;
  • You have an experimental mindset with a launch fast and iterate mentality. Extensive experience with designing and running experiments is essential;
  • 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 over a wide range of audiences;
  • You stay up-to-date with the latest research and developments in the machine learning field, and apply this where valuable.

This role is based out of Adyen’s Amsterdam office. Adyen is an office-first company and values in-person collaboration; remote-only roles are not offered.

We took an unobvious approach to starting a payments company, building a platform from scratch. Today, we're the payments platform of choice for the world's brightest companies. Our unobvious approach is a product of our diverse perspectives. This diversity, of backgrounds, cultures, and perspectives, is essential in helping us maintain our momentum.

Finance & Banking
Amsterdam
Active in 22 countries
1,700 employees
60% men - 40% women
Average age is 31 years