Job Description
Requirements:
- A degree in Data Science, Statistics, Mathematics, or a related quantitative discipline
- A minimum of 3 years of experience in Data Science, Risk Analytics, or Credit Risk Management.
- Experience building and validating credit risk models, including scorecards and provisioning.
- Proficiency in Databricks, SQL, R, or Python.
- Familiarity with IFRS 9, Basel, or equivalent credit risk regulatory frameworks.
- Exposure to cloud-based data platforms (AWS, GCP, Azure).
- Strong background in statistical modelling, machine learning, and predictive analytics.
- Knowledge of advanced machine learning techniques and model interpretability methods.
Responsibilities:
- Develop, implement, and maintain acquisition scorecards to evaluate MCA applicants.
- Monitor provision models aligned with regulatory and accounting standards.
- Enhance portfolio monitoring tools to track credit performance and early warning signals.
- Analyse transaction data, repayment patterns, and business health metrics to inform risk strategies.
- Identify trends, correlations, and anomalies that impact credit performance and portfolio stability.
- Collaborate with product, finance, and operations teams to embed data-driven decision-making.
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