Senior Credit Card Risk Prevention Specialist

3 days ago

Thiruvananthapuram, Kerala, India beBeeRisk Full time ₹ 15,00,000 - ₹ 22,50,000

Job Title: Senior Fraud Risk Modeler (Credit Card)

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About the Role:

We are seeking a highly skilled Senior Fraud Risk Modeler to design, develop, and maintain models to detect and prevent fraud across various financial products and channels. The successful candidate will be responsible for developing, implementing, and validating fraud detection and prevention models using advanced statistical and machine learning techniques for credit card products.

Key Responsibilities:

  • Model Development & Validation: Build, implement, and validate fraud detection and prevention models using advanced statistical and machine learning techniques for credit card products.
  • Data Analysis & Interpretation: Analyze large-scale transactional and behavioral data to identify fraud patterns, assess model performance, and provide actionable insights.
  • Risk Assessment & Monitoring: Evaluate existing fraud controls, monitor fraud trends, and quantify exposure to evolving threats across digital and traditional channels.
  • Communication & Collaboration: Effectively present analytical findings and model performance to both technical and non-technical stakeholders.
  • Documentation & Reporting: Maintain comprehensive documentation of model development processes, risk assumptions, fraud detection frameworks, and compliance requirements.
  • Technical Skills: Strong proficiency in Python, SQL, and data science tools; familiarity with real-time decision engines and fraud detection platforms is a plus.
  • Domain Expertise: Deep understanding of fraud domain expertise for debit card product.
  • Leadership & Teamwork: Ability to lead fraud analytics initiatives, mentor junior analysts or data scientists, and collaborate with risk, IT, and fraud operations teams.

Qualifications:

  • 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.

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