Credit Risk Data Scientist: Predictive Modeling & Dashboard

Network Finance; Randburg; On-site; ZAR 650,000 - 950,000; Full time

Job summary

Network Finance is seeking a technically strong Credit Risk Data Scientist to join our growing risk analytics team. You will contribute to development, monitoring, and enhancement of credit risk models across the customer lifecycle.

This role offers exposure to a broad range of analytics, portfolio monitoring, automated reporting, and data-driven recommendations to influence business decisions. Ideal candidates have 3–6 years in data science or credit risk within banking or fintech and strong

Qualifications

• Degree in Statistics, Mathematics, Data Science, or a quantitative field.
• 3–6 years in Data Science, Credit Risk Analytics, or related roles.
• Experience in Banking/FinTech lending or credit risk environments; predictive models and scorecards.

Responsibilities

• Develop, enhance, and monitor credit risk models across the customer lifecycle.
• Perform portfolio analysis to identify trends, risk drivers, and improvement opportunities.
• Conduct exploratory data analysis, feature engineering, segmentation, and model monitoring.
• Support model validation, back-testing, calibration, and governance activities.
• Develop automated reports, dashboards, and recurring analytical outputs.
• Build BI dashboards to support portfolio monitoring and performance management.

Skills

Advanced SQL

Python

SAS

Predictive modelling

Statistical analysis

Portfolio analytics

Stakeholder engagement

Communication

Data storytelling

Education

Degree in Statistics or Mathematics or Data Science

Tools

Power BI

Tableau

SAS Studio

Job description

Network Finance is seeking a technically strong Credit Risk Data Scientist to join our growing risk analytics team. You will contribute to development, monitoring, and enhancement of credit risk models across the customer lifecycle.

This role offers exposure to a broad range of analytics, portfolio monitoring, automated reporting, and data-driven recommendations to influence business decisions. Ideal candidates have 3–6 years in data science or credit risk within banking or fintech and strong