Expert Credit Card Fraud Analyst

19 hours ago

Vellore, Tamil Nadu, India beBeeFraud Full time ₹ 1,50,00,000 - ₹ 2,00,00,000

Senior Fraud Risk Modeler Overview

We are seeking an experienced Senior Fraud Risk Modeler to join our team. As a key member of our fraud prevention group, you will be responsible for designing, developing, and maintaining models to detect and prevent fraud across various financial products and channels.

Your primary objective will be to analyze emerging fraud trends, assess fraud risk, and support fraud prevention strategies while effectively communicating insights to stakeholders and collaborating with cross-functional teams.

  • Fraud Detection and Prevention: Develop, implement, and validate advanced statistical and machine learning techniques for credit card products to identify and prevent fraudulent activity.
  • Data Analysis and Interpretation: Analyze large-scale transactional and behavioral data to identify patterns, assess model performance, and provide actionable insights to inform business decisions.
  • Risk Assessment and Monitoring: Evaluate existing fraud controls, monitor fraud trends, and quantify exposure to evolving threats across digital and traditional channels.
  • Communication and Collaboration: Present analytical findings and model performance to technical and non-technical stakeholders, including fraud operations, compliance, and executive leadership.
  • Documentation and Reporting: Maintain comprehensive documentation of model development processes, risk assumptions, fraud detection frameworks, and compliance requirements.

Requirements

  • Bachelor's or Master's degree in a quantitative discipline such as Statistics, Mathematics, Computer Science, Economics, Data Science, or a related field.
  • 6 to 7 years of hands-on experience in a banking environment, specifically in developing, implementing, and maintaining fraud risk models across products and channels.
  • Proven experience in fraud analytics and modelling, including transaction monitoring, real-time detection, and rules-based or machine learning-driven approaches.
  • Strong programming skills in Python, SQL, R, or SAS for model development, data manipulation, and automation.

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