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Predictive Analytics and Portfolio Risk Manager

  • Hybrid
    • Maadi, Al Qāhirah, Egypt
  • Credit

Job description

Summary:

Leading and managing predictive analytics initiatives and credit risk strategies. This role is responsible for developing models, algorithms, and strategies to enhance customer risk assessments and optimize credit decisions. The Head of Predictive Analytics and Credit Risk ensures the organization has effective credit risk management practices in place to minimize losses and maintain a healthy portfolio across two operating markets (Egypt & KSA).

Roles and Responsibilities:

  1. Develop Predictive Analytics Models:

  • Lead the development and implementation of predictive analytics models and algorithms to assess customer creditworthiness, behavior, and propensity to default.

  • Collaborate with data scientists and analysts to gather, clean, and analyze data for model development.

  • Continuously monitor and fine-tune models for accuracy and effectiveness.

2. Credit Risk Strategy Management:

  • Implement automated underwriting processes, leveraging machine learning algorithms and artificial intelligence to streamline credit decision-making

  • Define and implement credit risk strategies aligning with the company's risk appetite and regulatory frameworks.

3. Portfolio Performance Monitoring:

  • Establish key performance indicators (KPIs) and monitor portfolio performance against targets in real-time, utilizing automated monitoring systems and alerts to identify potential risks and define proactive measures

  • Analyze credit performance metrics, such as credit losses, delinquency rates, and charge-offs, and provide meaningful insights and recommendations to senior management.

  • Develop reports and dashboards to communicate credit risk performance to relevant stakeholders.

  • Conduct regular portfolio reviews to identify potential risks, opportunities, and market trends.

4. Cross-Functional Collaboration:

  • Collaborate closely with stakeholders from different teams, such as product, marketing, finance, and operations, to develop strategies that balance credit risk and business growth.

  • Provide timely and valuable insights to support product development, marketing campaigns, and customer segmentation efforts.

5. Team Leadership:

  • Lead a team of data scientists, risk analysts, and credit specialists, providing guidance, mentoring, and training to drive performance and professional growth.

  • Foster a culture of innovation and continuous learning within the team.

Job requirements

  • Bachelor's degree in a quantitative field, such as mathematics, statistics, finance, or related disciplines. A Master's or Ph.D. is a plus.

  • Extensive experience in predictive analytics, credit risk modeling, and credit risk management within the financial services industry, preferably in the BNPL or consumer lending space.

  • Strong analytical skills, with expertise in statistical modeling techniques, machine learning algorithms, and data analysis.

  • Knowledge of relevant programming languages and tools such as Python, R, SQL, and data visualization tools.

  • Familiarity with credit risk regulations and industry best practices.

  • Excellent communication and presentation skills, with the ability to translate complex concepts into actionable insights for various stakeholders.

  • Strong leadership and people management skills.

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