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Financing Analytics & Modeling Division Head

  • Lead the development and implementation of financing analytics models (credit scoring, risk rating, and behavioral scoring) to support data-driven decision making.
  • Oversee financing portfolio analysis to monitor asset quality, debtor performance, and risk trends in support of mitigation strategies.
  • Manage a team of data scientists and analysts in executing analytics projects, including data preparation, modeling, evaluation, and model deployment into production systems.
  • Coordinate with related divisions such as Risk Management, Financing, and IT in developing policies, model parameters, and analytics data infrastructure.
  • Drive innovation and the implementation of AI/ML technologies to improve the efficiency, accuracy, and speed of financing analysis processes.
  • Conduct credit risk measurement on internal models applied to financing products that utilize scoring systems to ensure accurate quality assessments and minimize potential bank losses.
  • Develop and monitor internal models for financing products that use scoring systems, anticipate potential challenges and risks, and take prompt mitigation actions.

Requirements

  • Minimum 5 years of experience in data analytics, risk management, or credit scoring model development within the financial services, banking, or fintech industry.
  • Proven experience in building and maintaining credit risk models using advanced analytics and machine learning techniques.
  • Strong ability to process and analyze large-scale data to support strategic decision making.
  • Experience in regularly monitoring and evaluating model performance, as well as proposing enhancements to ensure model reliability.
  • Experience working in a multidisciplinary environment and collaborating with cross-functional teams such as Risk, Finance, and IT to generate actionable analytical insights.
  • Hands-on experience in implementing ETL (Extract, Transform, Load) processes to collect, process, and manage financing risk-related data.

What this application asks

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