Head of Fraud Analytics

Job Desc :

• Own and define Flip's fraud analytics strategy across all products, payment channels, and customer journeys.
• Lead the fraud analytics team responsible for transaction monitoring, fraud detection, rule optimization, fraud investigations, and fraud performance reporting.
• Develop scalable fraud monitoring frameworks, dashboards, and KPIs to continuously measure fraud exposure, operational effectiveness, and customer impact.
• Drive continuous optimization of fraud detection rules, machine learning signals, thresholds, and decision strategies to maximize fraud prevention while minimizing customer friction and false positives.
• Analyze large-scale transactional, behavioral, and operational datasets to identify fraud trends, attack patterns, emerging risks, and systemic vulnerabilities.
• Partner closely with Product, Engineering, Operations, Compliance, Data Science, and Business teams to embed fraud prevention into product design and operational processes.
• Provide strategic recommendations for new product launches, payment methods, customer journeys, and business initiatives from a fraud risk perspective.
• Lead fraud analytics support for regulatory reviews, audits, investigations, and compliance requirements, ensuring proper documentation and governance.
• Establish fraud governance processes, reporting standards, and executive-level risk communication.
• Drive continuous improvement in fraud detection methodologies by leveraging advanced analytics, automation, AI, and emerging technologies.
• Build, mentor, and develop a high-performing fraud analytics organization, fostering strong analytical capabilities, innovation, and ownership.
• Represent Fraud Analytics in executive discussions and serve as the primary advisor on fraud-related strategic decisions.

Requirement :

• 10+ years of experience in Fraud Analytics, Fraud Risk Management, Risk Analytics, or Financial Crime, preferably within fintech, payments, banking, digital banking, or consumer finance.
• Proven experience leading fraud analytics teams and managing fraud strategies at an organizational level.
• Deep understanding of payment ecosystems, fraud typologies, transaction monitoring, authentication, chargebacks, account takeover, mule detection, scams, and digital payment fraud.
• Strong expertise in fraud analytics, fraud detection methodologies, fraud operations, and fraud performance management.
• Advanced analytical and problem-solving skills with experience working with large-scale transactional and behavioral datasets.
• Strong SQL proficiency and familiarity with Python, R, or similar analytical tools. 
• Hands-on coding experience is preferred but the ability to lead technical analytics initiatives is essential.
• Experience designing fraud rules, detection strategies, fraud KPIs, and fraud decision frameworks.
• Strong knowledge of regulatory requirements related to fraud prevention, AML, payment risk, and financial crime.
• Experience collaborating with regulators, auditors, compliance teams, and external partners.
• Excellent communication and stakeholder management skills, with the ability to influence senior leadership and translate complex analytical insights into business decisions.
• Proven track record of building, mentoring, and leading high-performing analytics teams.
• Strategic mindset with the ability to balance customer experience, business growth, operational efficiency, and fraud risk.