Data Scientist | On-site | George, Western Cape at Badger Holdings (Pty) Ltd

Your day-to-day will include:

• Preparing and transforming data for machine learning (cleaning, feature engineering, optimisation)
• Conducting exploratory analysis to uncover trends and guide model design
• Building, testing, and deploying machine learning models aligned to business needs
• Collaborating with actuarial teams to align assumptions and modelling approaches
• Validating models and ensuring performance, accuracy, and reliability
• Monitoring live models for drift and performance degradation
• Maintaining, retraining, and improving models over time
• Creating clear documentation for models, pipelines, and processes
• Developing dashboards and reporting tools to track performance and KPIs
• Communicating insights and recommendations to both technical and non-technical stakeholders

About you

You’re someone who enjoys solving real problems and not just building models for the sake of it. You’re curious about the “why” behind the data and motivated by the impact your work can have.

Requirements

Requirements:

• A degree (Honours preferred) in Data Science, Actuarial Science, Statistics, Mathematics, or a related field
• 3+ years’ experience in data science or machine learning roles
• Strong Python and R skills, with proven experience building and deploying models
• Solid experience across the full ML lifecycle (data → model → deployment)
• Hands-on experience with statistical modelling, machine learning, and time series forecasting
• The ability to translate technical outputs into clear business value
• Strong communication and stakeholder engagement skills, particularly with actuarial teams
• A proactive, energetic mindset and a genuine passion for data and innovation

Nice to have:

• Experience in insurance (especially short-term insurance)
• Exposure to CLTV modelling, claims modelling, survival analysis, or actuarial-related work
• Experience with dbt, Snowflake, GCP, or similar cloud platforms
• Familiarity with MLOps practices and machine learning platforms
• Experience with BI tools (Power BI, Tableau, Looker, Qlik, etc.)