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.
