Data Scientist

Job description

• 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.

• 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.

Requirements

• Banking

• Data Analysis

• Data Science

• Financial Services

• Machine Learning

• Python

• R

• Risk Analysis

• SQL

• Statistical Analysis