Risk Data Science, Director

THE POSITION
Our roster has an opening with your name on it

FanDuel is looking for a Risk Data Science Director to help shape our Risk & Trading team at America’s #1 Sportsbook. The role will include evolving customer and revenue outcomes through profiling and automation, owning the risk operating model, and ensuring a consistent, scalable approach to risk management across regions. You will leverage cutting edge tools and subject-matter expertise to ensure a best-in-class betting experience for our customers.

The role requires a strong knowledge of sports betting proven management experience. You will be a key member of the Risk & Trading leadership team, partnering closely with Trading, Quants, Analytics, Product, Compliance, and Growth team leaders to define priorities, drive cross-functional execution, and continuously improve how we manage risk. The role requires comfort operating in a fast-moving environment and will include work outside of normal business hours, including weekends.

In addition to the specific responsibilities outlined above, employees may be required to perform other such duties as assigned by the Company. This ensures operational flexibility and allows the Company to meet evolving business needs.

THE GAME PLAN
Everyone on our team has a part to play

Lead the Risk Data Science team

• Manage and develop a team of data scientists focused on customer risk profiling, anomaly detection, and risk automation across regions (e.g., Dublin/Melbourne/NJ), including hiring, onboarding, and long-term capability building.
• Set clear priorities, ensure role clarity, and drive measurable outcomes across the team.
• Build a culture of continuous improvement and accountability, focused on best-in-class technical standards and practices.

Drive risk data science strategy and execution

• Develop and drive risk data science strategy across Sportsbook aligned to business and product goals (revenue, margin, customer outcomes, responsible gaming, compliance).
• Partner with data engineering to modernize data infrastructure, reduce tech debt, and build scalable pipelines. Advance automation throughout risk operations.
• Support the risk operating model, including governance, decision forums, escalation mechanisms, and performance management cadence, with an eye toward improving inefficiencies.
• Establish clear, communicated policies and standards across regions (risk tolerance, profiling, errors, mitigation actions), ensuring consistent interpretation and execution.
• Develop strategies to derive and apply insights from bet information to improve pricing accuracy

Deliver measurable business outcomes