Behavioural Data Scientist Graduate at Discovery

Discovery Health is offering a high-impact career launchpad for analytically minded graduates through their Behavioural Data Scientist Graduate opportunity situated in Johannesburg and Cape Town, South Africa. Operating at the intersection of behavioural economics, clinical data, and cutting-edge digital health innovation, successful candidates will join the Digital and Discovery Health Care Services (DHCS) divisions. This vital role focuses on analysing complex datasets from the Discovery Health App, HealthID, and clinical platforms to understand member behaviour, build predictive models, and guide data-led healthcare interventions across millions of lives.

Key Responsibilities

• Analyze large-scale transactional and behavioural member data across digital platforms such as the Discovery Health App and HealthID to uncover actionable customer insights.

• Develop and execute journey analytics, member segmentation, and advanced predictive models to optimize clinical engagement and business outcomes.

• Conduct rigorous hypothesis testing, A/B experimentation, and regression analysis to evaluate product features and customer engagement strategies.

• Perform data preparation, cleaning, and feature engineering across relational and dimensional database architectures.

• Collaborate closely with cross-functional product, digital, and healthcare teams to translate complex business problems into actionable analytical solutions.

• Design intuitive data visualisations, reports, and dashboards to present statistical insights effectively to technical and non-technical stakeholders.

• Explore emerging analytical methodologies, including Natural Language Processing (NLP) and Generative AI, to enhance digital service delivery.

Why Join the Company

Discovery is globally celebrated for pioneering the Shared-Value Insurance model and maintaining a dynamic culture rooted in societal impact, innovation, and technological excellence. As a graduate at Discovery Health, you will collaborate with seasoned actuaries, machine learning practitioners, and digital strategists who mentor you through real-world, high-stakes analytics problems. Discovery provides access to enterprise-grade data infrastructures, clear career progression frameworks, world-class office facilities in Sandton and Cape Town, and a collaborative environment designed to turn ambitious graduates into leading industry data scientists.

Application Strategy (Exclusive)

• Showcase Behavioural & Practical Projects: Emphasise university capstones, GitHub repositories, or Kaggle competitions where you tackled human behaviour, churn prediction, or health analytics rather than generic toy datasets.

• Highlight Your Tooling Proficiency: Explicitly quantify your experience with Python, R, or SQL in your CV, detailing how you queried large datasets, performed data cleaning, and engineered features.

• Bridge Analytics with Business Impact: In your motivation or project summaries, demonstrate your ability to answer the question 'So what?' by showing how your statistical findings translate into strategic user decisions.

Interview Preparation

Candidates shortlisted for this position should prepare to answer technical and behavioural evaluation questions, such as:

• "How would you clean and evaluate a messy, real-world behavioural dataset before applying a predictive classification model?"

• "Can you describe an instance where you translated an ambiguous business or healthcare problem into a concrete hypothesis-testing framework?"

Sharpen your responses and practice your technical delivery using the YouthNextStep Interview Simulator.

How to Apply

Applicants must apply directly via the Discovery Careers portal before the role closes. Click here to apply for this role.

Salary is estimated based on market research.

• Bachelor’s degree in Data Science, Actuarial Science, Statistics, Computer Science, Engineering (Industrial, Aeronautical, Mechanical), or a related quantitative analytics degree.

• Foundational programming and querying skills in Python, R, or SQL.

• Solid understanding of core statistics, including regression analysis and hypothesis testing.

• Knowledge of machine learning fundamentals, model evaluation, and feature preparation.

• Strong problem-solving capability, logical thinking, and high attention to detail.

• Effective communication and stakeholder engagement skills to translate analytics into business value.

• Honours or Master’s degree is advantageous.

• Experience or understanding of data visualisation tools such as Power BI or Tableau is advantageous.

• Familiarity with relational vs. dimensional database architecture is advantageous.

• Exposure to Generative AI, Large Language Models (LLMs), or Natural Language Processing (NLP) is an added advantage.