Head of Casino Risk for B2Tech building and scaling global risk function across markets. Ensure operational resilience and profitability while collaborating with cross-functional teams.
Responsibilities
Own and execute the global casino risk strategy across all brands and markets, ensuring profit protection and risk control.
Build, structure, and scale the Casino Risk function, including team design, governance, and operational coverage.
Define and implement SOPs covering RTP monitoring, bonus abuse, provider risk, and incident management.
Monitor performance and risk exposure using data, KPIs, and alerts in close collaboration with BI teams.
Act as the primary escalation point for high-risk incidents, investigations, and complex casino-related events.
Lead coordination with providers, aggregators, and platform partners to ensure risk alignment and control.
Partner cross-functionally to embed risk controls into products, promotions, and operational workflows.
Drive continuous improvement across risk prevention, detection, and operational efficiency.
Develop and lead a high-performing team, fostering a strong risk culture and ownership mindset.
Requirements
At least 6–8 years of experience in risk management within iGaming, betting, or similar high-risk digital environments.
Strong understanding of casino platforms, game engines, and aggregation layers.
Proven ability to define and interpret KPIs, data models, and anomaly detection (e.g., RTP, volatility, bonus abuse).
Experience working with AI-driven fraud or risk systems, including scoring models and anomaly detection.
Demonstrated leadership experience building, scaling, and managing high-performing teams.
Strong analytical and problem-solving skills with the ability to make decisions based on complex data.
In-depth knowledge of gambling regulations, AML frameworks, and fraud prevention practices.
Excellent communication skills with the ability to influence stakeholders and present complex insights clearly.
Nice to have: Hands-on experience with fraud detection technologies (device fingerprinting, IP/VPN detection, behavioral signals).
Nice to have: Experience with fraud rule engines, case management systems, and alerting tools.
Nice to have: Strong experience working with BI tools and large datasets to identify patterns and optimize risk strategies.
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