Data Scientist
Location: Johannesburg
Closing Date: 13 January 2026
Responsibilities
- Supporting the lead engineers in building end-to-end solutions that automate the validation and benchmarking of insurance models and monitor risk exposure, such as:
- Supporting the development and maintenance of statistical and machine learning models to assess credit, market, operational, and emerging risks
- Building predictive models for early warning indicators of risk events
- Using LLM-based agents to parse regulatory changes and graph theory for fraud network detection
- Building robust ETL processes to ingest structured and unstructured data
- Ensuring data quality, integrity, and compliance with regulatory standards
- Collaborating with 1st Line and other stakeholders to develop best practice frameworks and policies
- Challenging data lineage and recommend improvements for reliability
- Refactoring legacy processes into clean, automated Python workflows
- Performing deep-dive analysis on specific risk themes (e.g., inflation trends, claim spikes) to support strategic decisions
- Collaborating with the Data Engineer to ensure models are production-ready and integrated into the core platform
- You love taking a raw dataset and turning it into a working model or dashboard
- You care about code quality. You understand that a model isn’t finished until the code is clean, versioned, and reproducible
- Comfortable with uncertainty and unstructured complex problems
- Eager to grow, learn, and experiment with new technologies and methodologies
- Comfortable with uncertainty and unstructured complex problems
- Understands how data drives commercial outcomes
- Understanding of risk management processes
- Keeps up with new tools, AI trends, and best practices
- Works fluidly across business and technical teams
- Delivers with discipline, quality, and impact
- Brings fresh ideas to complex challenges
- Makes sense of messy, ambiguous data environments
- Follows through and learns from feedback
- Simplifies, automates, and scales where possible
- Handles competing deadlines and tasks with resilience, structure, and delivery focus
Knowledge, Skills and Experience
Bachelor’s degree in one of the following (or equivalent experience):
- Data Science / Data Engineering
- Statistics
- Computer Science
- Actuarial Science
- Engineering
- Applied Mathematics
- Advantages – Risk Management
- 2+ years of experience in data science, data engineering, risk analytics, software engineering, or actuarial environments, preferably in financial services
- Strong experience with Python and SQL
- Comfortable working in a version-controlled environment with review processes
- Bonus: Exposure to Cloud platforms (Azure/AWS)
- Bonus: Familiarity with Generative AI/LLM APIs
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