The Intermediate Data Scientist will play a key role in leveraging Discovery’s rich clinical, demographic, and operational data to create innovative, data-driven solutions that enhance customer experience and operational efficiency. Using predictive modelling, machine learning, and advanced analytics, the role contributes directly to strategic initiatives that improve service delivery and support Discovery’s world-class operations.

This position sits within a highly specialised and growing analytics team focused on identifying opportunities to optimise client schemes and improve member engagement through data insights.

Key Responsibilities

Stakeholder Engagement & Business Understanding

• Collaborate with multiple stakeholders to understand healthcare, operational, and business data requirements
• Translate business challenges into data science problems and analytical solutions

Data Exploration & Insight Generation

• Analyse large structured and unstructured datasets to uncover actionable insights
• Identify opportunities to improve operational efficiency and enhance customer/member experiences
• Apply exploratory data analysis techniques to support decision-making

Machine Learning & Advanced Analytics

• Research and apply modern machine learning and AI techniques to real-world business problems
• Investigate and implement predictive models to support strategic initiatives
• Stay up to date with advancements in AI, ML, and Generative AI, including LLMs

LLM & Generative AI Applications

• Collaborate with product owners, project managers, and business stakeholders to identify use cases for LLMs
• Conduct research on state-of-the-art Generative AI techniques and apply findings to business challenges
• Prototype and support implementation of LLM-based solutions where applicable

Model Monitoring & Optimisation

• Monitor model performance and ensure ongoing accuracy and relevance
• Refine and improve data pipelines, processes, and databases where opportunities arise
• Support deployment and integration of models into production systems

Communication & Reporting

• Present analytical findings and model results in a clear, actionable manner for business stakeholders
• Develop visual, verbal, and written reports to support decision-making

Personal Attributes and Skills

• Strong proficiency in Python, R, or Scala for data science applications
• Advanced SQL skills for data extraction, transformation, and loading
• Strong understanding of statistical modelling and machine learning techniques
• Experience with big data systems and distributed computing concepts
• Familiarity with version control tools such as Git
• Strong analytical thinking and problem-solving abilities
• Ability to define problems and develop structured analytical approaches
• Excellent communication skills with the ability to present complex findings clearly
• Strong attention to detail and high level of accuracy
• Self-driven, curious, and passionate about data exploration
• Ability to work independently and collaboratively within a team
• Ability to manage multiple priorities in a fast-paced environment

Education and Experience

• Honours or Master’s degree in Computer Science, Data Science, Statistics, Applied Mathematics, or related quantitative field
• Alternative analytical qualifications considered if supported by relevant experience

Experience

• Minimum of 2 years’ experience in a Data Science or related analytical role
• Experience in statistical modelling, data mining, and machine learning
• Exposure to software engineering principles or working with large, complex datasets is advantageous

Employment Equity

The organisation is committed to diversity and equal opportunity. Applications from individuals with disabilities are encouraged, and all recruitment decisions are aligned with the approved Employment Equity Plan.