Straive - Senior Fraud Risk Modeler - Credit Card

Job Role : Senior Fraud Risk Modeler(Credit Card).

Experience : 5+ Years.

Location : Gurgaon / Bangalore.

• As a Senior Risk Modeler specializing in Fraud Risk, you will design, develop, and maintain 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.
• Technical Skills : Strong proficiency in Python, SQL, and data science tools; familiarity with real-time decision engines and fraud detection platforms is a plus (Actimize, Falcon, SAS).
• 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.
• Problem Solving : Proactively identify vulnerabilities in fraud strategies, recommend enhancements, and respond to emerging threats in a fast-paced environment.
• Adaptability : Stay current with the latest fraud schemes, detection technologies, and regulatory developments impacting fraud risk Bachelors or Master's 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.
• Good understanding of how linear regression and XGBoost work, including their assumptions, strengths, and limitations

(ref : iimjobs.com)