Fraud Model Monitoring

We are seeking a highly skilled and motivated Fraud Analytics and Machine Learning Enthusiasts to join our team. In this role, you will validate, monitor, document cutting-edge machine learning models and provide analytics solutions to detect, prevent, and mitigate fraud across banking products and services. The ideal candidate is passionate about leveraging data science and analytics to protect customers and enhance the banking and operational efficiency.

Responsibilities

• Validate and monitor predictive models for real-time fraud detection systems using valid monitoring metrics / KPI's.
• Prepare technical documents related to fraud models and model validation. Validate the models using various techniques and KPIs, out of time validation etc.
• Set up monthly / quarterly and annual monitoring for the models using valid monitoring metrics / KPI's.
• Perform Root Cause Analysis in case of deterioration of model performance / data issues.
• Evaluate and optimize existing ML models for performance, scalability, and explainability.
• Apply deep learning and advanced analytics for behavior analysis and risk profiling as part of
• Analyze transaction data to identify patterns, anomalies, and fraud trends.
• Perform exploratory data analysis (EDA) to understand customer behavior and potential fraud.
• Translate data-driven insights into actionable recommendations for leadership and stakeholders.
• Collaborate with other teams like fraud strategy to enhance fraud prevention frameworks.

Qualifications

Skills : fraud,validation,analytics,models,data,machine learning,kpi,learning

Skills Required

Machine Learning, Python, Fraud Analytics, Statistical Techniques