Job Description :

We are seeking a highly analytical and detail-oriented Fraud Strategy Analyst to join our growing Risk Analytics team. The role will focus on developing, optimizing, and monitoring fraud prevention strategies across customer acquisition, account management, payments, and digital transactions. The ideal candidate will leverage data-driven insights to identify emerging fraud trends, minimize fraud losses, and enhance customer experience while maintaining strong risk controls.

Key Responsibilities :

- Develop, implement, and refine fraud detection and prevention strategies using data analytics and risk-based decisioning.

- Analyze large datasets to identify fraud patterns, anomalies, and emerging threats across multiple channels.

- Design and monitor fraud rules, triggers, scorecards, and risk models to improve fraud detection effectiveness.

- Conduct deep-dive investigations into fraud incidents and recommend corrective actions.

- Perform strategy performance analysis, including fraud loss measurement, approval rate impact, and operational efficiency assessments.

- Collaborate with cross-functional teams including Product, Operations, Compliance, Engineering, and Business stakeholders to implement fraud mitigation solutions.

- Build dashboards, reports, and performance metrics to track key fraud and risk indicators.

- Support A/B testing, champion-challenger frameworks, and continuous optimization of fraud strategies.

- Ensure adherence to regulatory requirements, internal policies, and industry best practices.

Required Qualifications :

- Bachelors degree in Engineering, Statistics, Mathematics, Economics, Computer Science, or a related quantitative field.

- 2-6 years of experience in Fraud Analytics, Risk Analytics, Fraud Strategy, or Financial Crime Analytics.

- Strong proficiency in SQL for data extraction, manipulation, and analysis.

- Experience with analytical tools such as Python, R, SAS, or Excel.

- Knowledge of fraud risk management, transaction monitoring, identity verification, and payment fraud concepts.

- Strong problem-solving, stakeholder management, and communication skills.

Preferred Qualifications :

- Experience in Banking, FinTech, Payments, E-commerce, or Digital Lending.

- Exposure to machine learning, predictive modeling, and visualization tools such as Tableau or Power BI.

- Experience working in a global or US-based enterprise environment.