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Senior Credit Card Risk Modeling Specialist
2 weeks ago
Job Role : Senior Fraud Risk Modeler(Credit Card)
We are seeking an experienced and skilled Fraud Risk Modeler to join our team. The ideal candidate will have a strong background in fraud analytics, machine learning, and statistical modeling.
In this role, you will be responsible for designing, developing, and maintaining models to detect and prevent fraud across various financial products and channels - primarily in the credit card domain. You'll analyze emerging fraud trends, assess fraud risk, and support fraud prevention strategies, while clearly communicating insights to stakeholders and collaborating with cross-functional teams to enhance fraud detection capabilities and reduce fraud losses.
- 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, including fraud operations, compliance, and executive leadership.
- Documentation & Reporting: Maintain comprehensive documentation of model development processes, risk assumptions, fraud detection frameworks, and compliance requirements.
Required Skills & Qualifications:
- Bachelors 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.
- Proficiency with machine learning and statistical techniques such as decision trees, gradient boosting, clustering, anomaly detection, and neural networks.
Our company is a leading provider of innovative solutions for fraud prevention and detection. We are committed to delivering exceptional results and exceeding customer expectations.
Benefits
We offer a competitive salary, comprehensive benefits package, and opportunities for professional growth and development.
