The opportunity
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.
What you'll do
Framework Development: Collaborate with cross-functional data teams to develop scalable and reusable frameworks for evaluating large datasets on pressing business questions.
Data Analysis: Determine the necessary data required to solve a wide variety of business problems; extract required data, draw conclusions, and provide recommendations. Whether it’s providing insights to our key products or facilitating new experiments with our merchants, you’ll be driving new initiatives to help Adyen grow 20x.
Be a Subject Matter Expert: Act as Adyen’s SME for both merchants and internal stakeholders on payment optimization.
Data Strategy: Shape the next generation of BI and data infrastructure. Build self-service tools to enable business users and contribute to automation and scaling projects.
Storytelling: Turn your findings into effective communication and concise, actionable advice by connecting the data to a story. You will be presenting to internal customers, but also to our merchants (the biggest and well known brands in the world) directly.
Stakeholder Management: Collaborate with Account Managers, Product teams, and other Optimization Data Analysts to align on data best practices and priorities. Gather requirements, provide data insights, and address inquiries. Communicate findings, recommendations, and progress clearly and concisely.
What they're looking for
- You have at least 5 years of relevant working experience in the Data & Analytics field.
- You have excellent analytical and data wrangling skills, with advanced proficiency in PySpark/ Python.
- Experience using descriptive and inferential statistics (e.g., distributions,: correlations, hypothesis testing, regressions).
- Expertise in leveraging data to uncover meaningful and actionable insights,: paired with the ability to craft compelling data stories that effectively present findings and recommendations to executives, driving informed decision-making.
- Experience with data visualization platforms (e.g., Looker, Tableau).
- Familiarity with Big Data tools and platforms such as Spark and Airflow, and: proficiency in version control using Git.
- Ability to design and develop efficient and scalable ETL and data pipelines: for datasets, including the use of automated data validation to ensure reliability.
- Ability to manage multiple priorities and deliver results in a fast-paced environment.