Senior Fraud Analyst

BettingJobs is currently seeking a Senior Fraud Analyst for an established sports betting company. The successful candidate will play a key role in identifying, investigating, and mitigating fraudulent activity across the platform while helping improve fraud detection systems and processes. Key Responsibilities: Investigate complex fraud cases across player accounts, payments, and platform activity. Identify patterns of multi-accounting, promotional abuse, payment fraud, and bot activity within the iGaming ecosystem. Perform deep data analysis to detect emerging fraud trends and vulnerabilities. Conduct proactive fraud reviews using behavioral, transactional, and device data. Analyze large datasets to uncover fraud rings and coordinated abuse networks. Produce clear reports and actionable insights for internal stakeholders. Assist in the development of fraud prevention strategies and operational workflows. Support incident response efforts related to fraud attacks or abuse. Requirements: 5+ years of fraud prevention experience, preferably within the iGaming industry. Strong knowledge of common iGaming fraud schemes including: Multi-accounting Bonus abuse Payment fraud Identity manipulation Bot-driven account creation Advanced analytical and investigative skills. Proficiency Microsoft Excel for data analysis and reporting. Experience working with fraud detection platforms and risk scoring systems. Strong ability to interpret behavioral, transactional, and device-level data. Excellent problem-solving and critical thinking skills. Ability to communicate complex fraud findings clearly to technical and non-technical stakeholders. Nice to have: Experience with advanced data analysis tools such as: SQL Python R Neo4j or graph databases Experience performing network analysis to detect fraud rings. Familiarity with device fingerprinting, IP intelligence, and behavioral analytics. Experience working with fraud prevention tools such as SEON, Sift,or similar platforms. Experience building fraud detection models or automated monitoring systems.