Fraud Data Analyst
-
IT/Tech
Data Analyst -
Finance & Banking
Job Description & How to Apply Below
Location: Stonecrest
We are B2
Spin, 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. 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.
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.
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
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
(Big Query 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.
across Operations, Compliance and senior leadership, including the ability to challenge assumptions with data in a remote-team setting.
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.
PerformanceYour background, gender, age, race, ethnicity, disability, sexual orientation, religion, neurodiversity, or educational path will never be a barrier to joining us. Diversity fuels our innovation, collaboration, and growth, and we're committed to creating an environment where everyone can contribute their best work and thrive.
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