Payments & Fraud Data Analyst

We are B2Spin, and we are dedicated to delivering the best Free-to-Play Social Casino and gaming experiences by creating captivating, engaging, and unique products that are accessible to everyone. We have built a team of talented professionals from all over the globe, who are working to continually improve the experiences of our players. We are not looking to just be part of the industry, but to revolutionize it.

The role

B2Spin is looking for a Payments & Fraud Data Analyst to join our Business Intelligence team and help keep money moving safely through our platform. You’ll turn transactional and player-behaviour data into clear insight that improves payment performance, prevents fraud and abuse, and protects the experience for genuine players - working closely with Payments, Fraud, Compliance and Operations to make their decisions sharper and faster.

What you’ll do

• Own payment performance analytics end to end - diving into success rates, declines, payment methods and provider performance to surface improvements that reduce friction and cost.
• Uncover fraud and abuse patterns across transactional and behavioural data - from promo abuse and multi-accounting to chargebacks and money cycling - and translate findings into actionable rules, thresholds and segments.
• Design, back-test and monitor automated risk decisions, balancing fraud capture against player friction and tracking real-world impact after every change goes live.
• Build the reporting layer that keeps the business informed - dashboards in Looker or Tableau, plus alerts for business-critical anomalies like provider volume drops or risk spikes.
• Partner with Compliance on AML work, delivering investigation queries, data analysis and audit-ready reporting that hold up to scrutiny.
• Accelerate Operations and Customer Service with analytics that quantify review workloads, case outcomes and player-facing friction so teams move faster and more consistently.
• Raise the analytical bar across the business - documenting data sources, metric definitions and automation logic so insight is trusted, reusable and easy to build on.

• Hands-on data analyst background in payments, fraud, risk or AML - ideally within gaming, iGaming, fintech or another high-volume digital environment.
• Strong SQL skills on a cloud data warehouse (BigQuery preferred) paired with practical experience in Looker, Tableau or Power BI.
• Demonstrated experience analysing fraud and abuse patterns in transactional and behavioural data, with a clear understanding of the trade-off between fraud capture and friction for genuine players.
• The ability to run analytical projects from ambiguity to delivery - scoping unclear questions, building solutions, documenting them and monitoring their impact over time.
• Confident, clear communication across Operations, Compliance and senior leadership, including the ability to challenge assumptions with data in a remote-team setting.
• An investigative instinct and sharp attention to detail - you notice when something looks off and you follow it until you understand why.
• Python for deeper analysis, anomaly detection or modelling is a strong plus, as is familiarity with fraud-scoring tools, device or behavioural signals, social casino mechanics, or ML approaches to fraud detection.