Senior Optimization Data Analyst

Join Adyen, a leading global payment company, as a Senior Optimization Data Analyst. In this role, you will drive payment performance for complex merchants, lead the team's most complex merchant engagements, and work directly with large-scale transactional data. You will collaborate with product teams, contribute to building an analytical layer, and drive the quality and rigor of the team's analytical work. Additionally, you will lead automation initiatives, develop playbooks, and maintain a forward-looking perspective on risk and fraud optimization.

Lead the Performance Optimization team's most complex merchant engagements in the risk, fraud, and ML optimization domain, designing and interpreting sophisticated analyses.

Drive the quality and rigor of the team's analytical work in the risk and fraud domain, designing and executing advanced data analyses, A/B tests, and statistical investigations.

The ideal candidate has a track record of driving measurable outcomes through data analytics in payments or fintech, with deep hands-on experience working with large-scale transactional data, and ML-based risk data

About Adyen

A track record of making the people and teams around you more capable: through mentorship, knowledge transfer, methodology development, and tooling that scales your expertise beyond your own direct output

Responsibilities

• Work directly with large-scale risk model data to analyze model behavior, detect performance patterns, and generate insights across merchant segments.
• They operate with a high degree of autonomy, owning complex analytical problems end to end from scoping through to recommendation, without requiring active direction to make progress. And they bring the ability to translate what the data reveals into strategies that merchants and internal teams can understand and act on
• This work requires the ability to go beyond standard analytics and work with raw, complex data to surface what is not yet visible
• Deep understanding of statistical methods including hypothesis testing, experiment design, regression modeling, and the ability to apply these rigorously in a business context where decisions have commercial consequences
• A forward-looking perspective on where payments risk and fraud optimization are heading, including familiarity with how ML adoption is reshaping risk strategy, how authentication frameworks are evolving under regulatory and commercial pressure, and how emerging payment patterns such as agentic commerce introduce new fraud and dispute challenges

Requirements

• Deep expertise in risk and fraud analytics, including hands-on experience working with ML-based decisioning systems and large-scale risk model data. You are comfortable working with raw model output and labeled risk data to generate insights that go beyond standard analytics
• Demonstrated ability to work at the boundary of technical and commercial: translating complex analytical findings into merchant-facing recommendations, product feedback, and strategic narratives that influence decisions at the senior level
• Experience with big data technologies including Spark and Airflow, and version control systems including Git, with a standard of engineering quality that produces reliable, maintainable, and scalable outputs
• Proven ability to lead high-impact, cross-functional initiatives independently, with the organizational credibility and communication skills to align stakeholders across commercial, product, and data functions
• 10+ years of relevant experience in data analytics, data science, risk, or fraud optimization, with a demonstrated track record of driving measurable impact in a payments or fintech environment
• Ownership mentality, intellectual curiosity, and the ability to operate in a fast-paced, cross-functional, global environment where ambiguity is the norm and impact is the measure
• Expert-level proficiency in Python, SQL, and PySpark, with hands-on experience in large-scale data processing, scalable ETL pipeline development, and production-grade analytical systems
• Strong experience with data visualization and self-service analytics tools such as Looker or Tableau, with the ability to design dashboards and tools that non-technical stakeholders can use independently

Preferred

• Payments or fintech industry experience is required at this level, not a plus

Pay

USD 154,000 - 200,000