Senior Data Scientist

Adyen is looking for a senior data scientist with deep expertise in statistical hypothesis testing, experimental design, and quantitative research methods to join the Experimentation Platform team in Amsterdam. We want to significantly increase the breadth of Experimentation at Adyen and that requires cutting-edge statistics. You will help to research and implement innovative hypothesis testing approaches that drive experimentation at industry-leading scale. You will also work with a diverse set of users, advocating and mentoring on best practices in experimental design, interpretation of results, and evidence-based decision-making.

In this role, you will:

• Research and implement industry-leading statistical methods to provide robust statistical signals across multiple business domains and contexts, optimising for time-to-signal and experiment quality;
• Develop and apply a deep knowledge of Adyen’s specific domain context in order to prioritise statistical methodologies and approaches that maximise business value;
• Stay up-to-date with the latest research and developments in statistical hypothesis testing;
• Collaborate closely with your multi-disciplinary team of backend/frontend/data engineers to help scope and define requirements for new platform features, ensuring statistical methods are integrated appropriately;
• Collaborate with data scientists across Adyen to identify opportunities for the novel application of statistical and data science techniques to challenging problems;
• Work closely with platform users to provide guidance and enable them for success; promoting experiment-driven culture and product development practices.

Who You Are:

• You have 7+ years of experience as a data scientist, including 2+ years working on an experimentation platform (or similar);
• You have a Master’s or Ph.D. in Statistics, Mathematics, Data Science, Computer Science, or a related quantitative field;
• You have a strong theoretical understanding of advanced frequentist and Bayesian hypothesis testing (e.g. sequential testing, e-processes, etc) as well as causal inference techniques and a proven track record of implementing such methods at scale;
• You have experience designing and analysing controlled experiments in an applied setting to provide tangible business outcomes;
• You have experience leveraging a big data framework to create the pipelines needed to gather experiment data;
• You have a strong understanding of software engineering practices as well as data engineering principles;
• You have strong familiarity with the standard data science toolkit, such as (py)spark, Pandas, SciPy, numpy, and Airflow;
• You have an experimental mindset with a launch fast and iterate mentality;
• You have proven experience in leading 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.