Product Manager - Fraud Detection & Operational Intelligence

Responsibilities

• Run discovery with operators, fraud/risk teams, compliance stakeholders, analysts, casino teams, payment teams, and internal experts to understand real operational workflows.
• Define and maintain product artefacts covering problem statements, user journeys, workflows, success metrics, constraints, assumptions, trade‑offs, and decisions.
• Translate fraud, AML, payments, gameplay, bonus abuse, and operator intelligence requirements into clear product requirements for design and engineering.
• Shape Shield’s risk decisioning capabilities, including risk scores, rule logic, case queues, review flows, reason codes, audit logs, operator permissions, and escalation paths.
• Shape Insights’ operator intelligence capabilities, including monitoring views, KPI definitions, report formats, alert logic, baseline comparisons, and AI‑assisted explanations.
• Partner closely with the data and AI Technical Product Manager, delivering clear data and AI requirements so Shield and Insights get the technical support they need.
• Use data actively and critically, ensuring tracking reflects reality and turning operational insights into concrete product decisions.
• Engage stakeholders with clarity and intent, gathering input while retaining ownership of prioritisation and trade‑offs.

Requirements

• 3+ years in a Product Management role.
• Experience owning or significantly contributing to fraud, risk, compliance, AML, payments risk, transaction monitoring, decisioning, or case management products.
• Experience working on products with complex backend logic, data dependencies, rules, scoring, workflows, or operational decision‑making.
• Strong understanding of Product Management fundamentals, including discovery, requirements definition, prioritisation, delivery, stakeholder management, and iteration.
• Strong data fluency and the ability to turn operational insight into clear product decisions.
• Comfort operating in environments with compliance, regulatory, financial, or high‑trust constraints.
• iGaming, casino, sportsbook, or gambling platform experience.
• Experience with AML/KYT, wallet risk, KYC, identity risk, device intelligence, payment fraud, chargebacks, or withdrawal risk.
• Experience with rules engines, risk scoring, fraud review tools, compliance tooling, or case management systems.
• Experience with third‑party risk or fraud providers such as Chainalysis, TRM, Elliptic, SEON, FingerprintJS, ThreatMetrix, Sumsub, Onfido, PSPs, or onramp providers.
• Exposure to bonus abuse, multi‑accounting, gameplay risk, shared wallet/payment method detection, account velocity, or operator back‑office workflows.
• Experience building dashboards, reports, alerts, anomaly detection, or operator intelligence products.
• Experience in B2B, SaaS, platform, or white‑label environments.
• Practical AI literacy, especially around AI‑assisted analysis, summaries, alerts, or decision‑support workflows.