Fraud Model Monitoring

6 hours ago

Bengaluru, Karnataka, India CG-VAK Software & Exports Ltd. Full time ₹ 12,00,000 - ₹ 36,00,000 per year

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

  • 5+ years of experience in analytics preferably in Banking and Financial Services
  • A minimum of 5 years of hands-on experience working on monitoring and validation of Machine Learning models to solve analytical use cases.
  • Solid understanding of banking products, fraud types (e.g., account takeover, synthetic fraud, identity theft), and transaction systems.
  • Knowledge of various statistical techniques used in analytics (regression, ML Models, Monitoring Metrics like KS, PSI, CSI, MAPE, Confusion Metrics etc.)
  • Excellent problem-solving and analytical skills, with the ability to work on complex projects and deliver high-quality results.
  • Proficiency in programming languages such as Python, and experience with ML related libraries.
  • Experience with large-scale data processing and distributed computing frameworks is a plus.
  • Strong communication skills, both written and verbal, with the ability to convey complex ideas to diverse stakeholders.

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

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