AML - Data Scientist

Job Title: AML - Specialist Data Scientist

Contract: 12-Month Contract

Location:
Midrand (Hybrid)

Role Purpose

We are seeking a highly analytical and commercially minded Specialist Data Scientist to drive the development of advanced analytics, machine learning, and AI-driven solutions that deliver business value and enhance customer experience.

This role will focus on leveraging big data to build personalised, contextual, and intelligent solutions across consumer, merchant, financial services, and digital product portfolios. The successful candidate will work cross-functionally with commercial, engineering, data, and technology teams to develop predictive models, automate insights, and support strategic decision-making.

Key Responsibilities

• Develop Machine Learning and AI solutions that generate actionable business insights and drive personalisation.
• Build predictive models using large, complex, and diverse datasets.
• Develop and deploy machine learning models across various business domains.
• Write prototype and production-level code (e.g., PySpark) for automated model training and scoring.
• Track, monitor, and report on machine learning model performance.
• Use data visualisation techniques to communicate insights effectively and support data-driven storytelling.
• Collaborate with Data Engineering teams to support data ingestion and model productionisation.
• Work closely with stakeholders to deliver analytics solutions aligned to business objectives.
• Manage and take ownership of a portfolio of data science initiatives from development through to stakeholder engagement.
• Contribute to broader AI and Machine Learning capability development within the organisation.

Core Competencies & Experience

• Minimum 3+ years experience in Data Science or Statistical Modelling.
• Strong experience analysing and manipulating large, complex datasets.
• Proven ability to build and deploy predictive models (e.g., Churn, AML, Credit Risk, Fraud).
• Strong data visualisation skills with ability to present insights clearly.
• Commercial understanding of how AI & ML drive business value.
• Strong stakeholder management and communication skills.
• Ability to work effectively in a fast-paced environment.
• Analytical mindset with strong problem-solving capability.

Technical & Professional Requirements

• Bachelors or Masters Degree in Mathematics, Statistics, Economics, Computer Science, Engineering, Artificial Intelligence, or related quantitative field (essential).
• Professional or academic experience in Big Data analytics and deployment of models in real-world environments.
• Proficiency in Python or R.
• Experience with SQL, Spark, SAS or similar large dataset technologies.
• Experience with machine learning libraries such as H2O, scikit-learn, PyTorch.
• Experience with modelling techniques including:
• Random Forest
• Gradient Boosting
• K-means Segmentation
• Regression Analysis
• Factor Analysis
• Time-Series Forecasting
• Familiarity with visualisation tools such as Tableau, Qlik, or Power BI.