Data Scientist

THE SKILLS MINE; Cape Town; On-site; ZAR 600 000 - 800 000; Full time

Job summary

A data-driven consultancy in Cape Town is seeking a Data Scientist with at least 3 years of experience in Data Science and Risk Analytics. The candidate will develop and maintain credit risk models, analyze transaction data, and collaborate with various teams to enhance data-driven decision-making. Proficiency in SQL and Python, along with experience in building credit risk models, is essential.

Qualifications

• Minimum of 3 years of experience in Data Science, Risk Analytics, or Credit Risk Management.
• Experience in building and validating credit risk models.
• Familiarity with IFRS 9, Basel, or equivalent credit risk regulatory frameworks.

Responsibilities

• Develop, implement, and maintain acquisition scorecards for MCA applicants.
• Monitor provision models aligned with regulatory and accounting standards.
• Enhance portfolio monitoring tools to track credit performance.

Skills

Data Science

Risk Analytics

Credit Risk Management

Statistical Modelling

Machine Learning

SQL

Python

Databricks

Education

Degree in Data Science, Statistics, Mathematics, or related quantitative discipline

Tools

Databricks

SQL

R

Python

AWS

GCP

Azure

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.