Data Scientist

Truffle; Stellenbosch; On-site; ZAR 600 000 - 900 000; Full time

Job summary

A financial services company in Stellenbosch is seeking a Data Scientist to join their analytics team. The role focuses on developing credit scoring models and requires extensive experience in data science, particularly in Python. Candidates should have strong knowledge of credit risk and be comfortable in fast-paced environments. The position offers opportunities for collaboration and innovation within the team.

Qualifications

• 5+ years’ experience in data science, focusing on credit modelling in Python.
• Strong grasp of the credit risk lifecycle and its business impacts.
• Ability to work effectively under tight timelines.

Responsibilities

• Develop, implement, and monitor credit scoring and predictive models.
• Design and deploy credit scorecards and behavioural models.
• Collaborate with data engineers for high-quality data pipelines.

Skills

Credit modelling

Python

Machine learning techniques

Data pipelines

Model validation

Fast-paced team experience

Education

Bachelor’s or Master’s degree in a STEM field

Tools

XGBoost

Scikit‑learn

Job description

Introduction

A prominent player in the financial services sector is expanding its credit modelling capabilities and seeking a highly capable Data Scientist to strengthen its analytics team. Renowned for its innovative use of data in driving strategic decision‑making, this organization offers a dynamic environment where cutting‑edge modelling and machine learning techniques are central to their approach. The team values collaboration, curiosity, and rapid delivery – and is looking for someone who thrives in high‑velocity environments with tangible impact.

Role Responsibilities

• Develop, implement, and monitor credit scoring and predictive models that directly shape business performance.
• Design and deploy credit scorecards and behavioural models to predict repayment performance.
• Leverage logistic regression and machine learning techniques such as XGBoost and Random Forests.
• Collaborate closely with data engineers to ensure model‑ready, high‑quality data pipelines.
• Ensure rigorous testing, validation, and monitoring of models in production.
• Support and contribute to a robust MLOps framework for rapid model deployment.

Experience Requirements

• 5+ years’ experience in data science, with a strong emphasis on credit modelling in Python.
• Proven track record in building, validating, and deploying models into production environments.
• Strong grasp of the credit risk lifecycle and relevant business impacts.
• Familiarity with ML tools and libraries (e.g. XGBoost, Scikit‑learn, etc.).
• Ability to work effectively under tight timelines (30‑day model delivery cycles are common).
• Preference will be given to candidates with experience in fast‑paced, high‑accountability teams.

Education Requirements

• Bachelor’s or Master’s degree in a STEM field (e.g., Actuarial Science, Mathematics, Statistics, Engineering, or related).
• PhD candidates will be considered if they can demonstrate applied, hands‑on modelling experience.

About Truffle

At Truffle, we specialise in connecting top actuarial and analytics professionals with exciting career opportunities.

By submitting your application, you consent to Truffle processing your personal information in line with the Protection of Personal Information Act (POPI).

If you have not received a response within two weeks, please consider your application unsuccessful.