Senior Machine Learning Scientist

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.

Adyen is looking for a Senior Machine Learning Scientist to join our team in Amsterdam, a person sitting at the cornerstone of algorithms, mathematics, and engineering, who can solve 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:

Optimize Intelligence at Adyen is a specialized team of Machine Learning Scientists and Data Analysts focused on maximizing transaction success, minimizing transaction costs, and driving payment performance at a global scale. We build and scale advanced ML/DL solutions that operate over massive, complex decision spaces, determining the optimal path for every single transaction in real time. Our systems evaluate high-dimensional data streams to dynamically select the optimal authentication methods, apply smart payment message optimizations, and orchestrate intelligent transaction routing. Our models live-score millions of daily transactions, balancing coupled cost and performance objectives simultaneously.

If you are passionate about solving intricate combinatorial challenges and pushing the boundaries of adaptive decision-making systems, join us in shaping the future of payments.

Identity and Verification Decisioning:

This is an opportunity to help define how Adyen makes identity decisions at global scale.

The team sits at the intersection of machine learning, distributed systems, fraud prevention, compliance, and customer experience. Rather than optimizing isolated models, you'll help build the intelligence that determines how millions of businesses and individuals are verified throughout their lifecycle.

You'll join a newly formed engineering team, giving you significant influence over the technical direction, architecture, and ML strategy from an early stage. Your work will directly impact fraud prevention, regulatory compliance, operational efficiency, and customer onboarding experience.

Dynamic Verification:

We are looking for a Senior Machine Learning Scientist to help build the machine learning capabilities behind Adyen's Identity Platform.

Adyen processes payments and financial events at global scale. To prevent fraud and financial crime effectively, we need to understand likely entities and relevant behavioural patterns across events, while maintaining a high bar for privacy, governance, reliability, and explainability. The Identity Platform develops shared capabilities that help Adyen understand which events and identifiers may belong to the same underlying person or actor. These capabilities serve multiple downstream teams and use cases, including real-time fraud prevention, AML detection, investigations, and future risk products.

You will help design and build the ML systems that make this possible. This includes applied modelling, large-scale data processing, low-latency serving, clear interfaces for downstream consumers, and the operational controls required for a platform used across teams.

This is a hands-on technical leadership role. You will influence long-term technical direction while remaining close to implementation, experimentation, and production systems.

• 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 our experiments, training runs, validation runs and monitoring before, during and after deployment. Furthermore, collaborate with MLOps to improve our 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 and 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.
  

Ensuring a smooth and enjoyable candidate experience is critical for us. We aim to get back to you regarding your application within 5 business days. Our interview process tends to take about 4 weeks to complete, but may fluctuate depending on the role. Learn more about our hiring process here. Don't be afraid to let us know if you need more flexibility.

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.