Data Analyst

Data Analyst – Revenue Assurance

Contract: 12 months

Location: Amsterdam (Hybrid – 2 days per week onsite)

Rate: Up to €105 per hour (based on a 40-hour week)

Overview

We’re working with a leading organisation looking for an experienced Data Analyst – Revenue Assurance to join their Revenue Assurance & Credit Risk function. This role plays a critical part in protecting revenue, identifying financial risk, and delivering scalable analytical solutions across the business.

You’ll sit at the intersection of data, finance, and payments, using advanced analytics to uncover revenue leakage, quantify financial exposure, and implement long-term controls. The role involves close collaboration with senior stakeholders across Finance, Product, FinTech, Commercial, Fraud, Tax and FP&A, translating complex data into clear, actionable insights.

Key Responsibilities

• Lead end-to-end analytical initiatives to identify, quantify and monitor revenue leakage and risk exposure
• Develop scalable analytics solutions, dashboards, and controls that move from hypothesis through to implementation
• Own analytics workstreams aligned to business priorities, from early concept through to delivery
• Partner with business stakeholders to turn ambiguous problems into structured analytical questions and success metrics
• Build clear, intuitive dashboards and reporting using tools such as Tableau, Grafana, or similar platforms
• Contribute to revenue assurance governance through high-quality analysis, reporting and presentations
• Manage a wide stakeholder group, clearly communicating complex findings and securing alignment on recommendations

Skills & Experience

• 4+ years’ experience in a data-driven or quantitative role, ideally within ecommerce, finance, banking or payments
• Strong academic background (MSc or PhD preferred) in a quantitative discipline such as Statistics, Mathematics, Econometrics, Computer Science, Engineering or similar
• Advanced SQL skills and strong experience with Python, PySpark and/or other analytical scripting languages
• Proven experience applying data mining and statistical techniques to solve real-world business problems
• Hands-on experience working with multiple data sources and data visualisation tools (e.g. Tableau)