Payments & Fraud Data Analyst

This is a fully remote position, open to applicants in Georgia, +3 more countries.

📋 Description

• Take ownership of payment performance analytics from beginning to end, covering success rates, declines, payment methods, and provider performance.

• Detect fraud and abuse trends through transactional and behavioral data analysis, including promotional abuse, multi-accounting, chargebacks, and money cycling.

• Convert insights into actionable rules, thresholds, and segments.

• Design, back-test, and oversee automated risk decision-making processes.

• Balance the capture of fraud with player experience and monitor the real-world effects after implementing changes.

• Create dashboards in Looker or Tableau and set alerts for critical business anomalies.

• Collaborate with Compliance on AML investigations, data analysis, and preparing audit-ready reports.

• Offer analytics on review workloads, case outcomes, and player-facing friction for the Operations and Customer Service teams.

• Document data sources, metric definitions, and automation logic.

• Work in partnership with Payments, Fraud, Compliance, and Operations teams.

⛳️ Requirements

• Hands-on experience as a data analyst in payments, fraud, risk, or AML.

• Ideally, experience within the gaming, iGaming, fintech, or another high-volume digital sector.

• Strong SQL skills on a cloud data warehouse, with a preference for BigQuery.

• Practical experience using Looker, Tableau, or Power BI.

• Proven experience in analyzing fraud and abuse patterns in transactional and behavioral data.

• Understanding of the balance between capturing fraud and minimizing friction for genuine players.

• Capability to manage analytical projects from initial ambiguity to final delivery.

• Skill in defining unclear questions, developing solutions, documenting them, and monitoring their impact over time.

• Clear communication skills with Operations, Compliance, and senior leadership.

• Ability to challenge assumptions with data in a remote team environment.

• Strong investigative instincts and keen attention to detail.

• Proficiency in Python for advanced analysis, anomaly detection, or modeling is a significant advantage.

• Familiarity with fraud-scoring tools, device or behavioral signals, social casino mechanics, or machine learning approaches to fraud detection is a plus.

• Required SQL proficiency to be included in the application form.

• Required hands-on experience in payments, fraud, risk, or AML to be included in the application form.

• A LinkedIn account link is required.

🏝️ Benefits

• Equal-opportunity hiring based on skills, motivation, and ideas.

• Flexible remote work arrangement.

• Opportunity to collaborate with a global team.

• Option for future-role contact consent for up to 12 months (optional).