Senior Machine Learning Scientist

Join Adyen, a leading global payment company, as a Senior Machine Learning Scientist. In this role, you will design and implement production-ready machine learning solutions, build and deploy algorithms, and collaborate with product managers and business stakeholders. You will work at the intersection of Big Data and actionable intelligence, leveraging Adyen's global payment flow to optimize payment performance.

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 stay up-to-date with the latest research and developments in the machine learning field, and apply this where valuable

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

Studies show that women and members of underrepresented communities apply for jobs only if they meet 100% of the qualifications. Does this sound like you? If so, Adyen encourages you to reconsider and apply. We look forward to your application!

About Adyen

If you have a strong machine learning background and love solving complex problems, we want to hear from you

Responsibilities

• Research, design, implement, train, deploy and monitor machine learning algorithms for various applications.
• 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.

Requirements

• You have an experimental mindset with a launch fast and iterate mentality. Extensive experience with designing and running experiments is essential
• You have 5+ years of experience as a machine learning or data scientist
• You have experience leveraging a big data framework to create the pipelines needed to feed the models with appropriate data
• You have experience with the full machine learning model lifecycle in production flows
• You have a good understanding of software engineering practices as well as data engineering and MLOps principles
• 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