Data Scientist

Build a successful career with us

We’re all about building strong, lasting relationships with our employees. We know that you have hopes for your future – your career, your personal development and of achieving great things. We pride ourselves in helping  our employees to realise their worth.
Through its five business clusters – Sanlam Fintech, Sanlam Life and Savings, Sanlam Investment Group, Sanlam Allianz, Santam, as well as MiWay and the Group Office – the group provides many opportunities for growth and development.

What will you do?

An exciting new opportunity exists in the MiWay Operational Analytics team. We are continuously looking to enhance operational efficiencies and improve business performance. Come join the team and be part of the challenge.

What will make you successful in this role?

Minimum Requirements  
Qualification Required  
• Bachelor's Degree or Honours in Mathematical Statistics, Data Science, Actuarial Science, Computer   
Science, or a related quantitative field.  

Minimum Experience  
• Minimum of 3–5 years in a data science, advanced analytics, or related quantitative role.   
• Demonstrable experience building and deploying predictive or classification models in a business   
environment.   
• Experience within the Short-Term Insurance or broader Financial Services industry is advantageous. 

Deliverables

The data scientist will contribute meaningfully to the analytics capability of the  Operational Analytics team. Key deliverables include:

• Predictive modelling: Build, validate, implement, and maintain propensity, classification, and regression models to support sales and operational decision making.  
• Model lifecycle management: Continuously monitor, retrain, and improve existing models, ensuring methodology and performance remain current and robust.  
• Data analysis & reporting: Perform in-depth data analysis and develop insightful reporting focused on operational and sales performance metrics.  
• Experimentation & strategy design: Identify, design, and pilot initiatives to optimise lead performance, customer engagement, and channel strategy through  A/B testing and other experimental frameworks.  
• Lead optimisation: Perform and refine monthly outbound lead selections on internally scored datasets, and design strategies to optimise lead usage across company sales channels.  
• Stakeholder collaboration: Partner with internal teams and external providers to better utilise, enrich, and optimise data assets and lead sources.  
• Ad-hoc analysis: Provide support for ad-hoc operational and sales-related analytical queries  

Competencies Required

• Strong understanding of statistical theory underpinning predictive and classification modelling (e.g., logistic regression, decision trees, ensemble methods, clustering).   
• Proficiency in Python for data manipulation, modelling, and visualisation.   
• Strong SQL skills (MS SQL / Oracle) for data extraction, transformation, and analysis.   
• Familiarity with model deployment pipelines and version control (e.g., Git).   
• Experience with BI/visualisation tools (e.g., Power BI) is advantageous.   
• Analytical and critical thinker with a curious, problem-solving mindset.   
• Strong attention to detail with the ability to validate and quality-assure analytical outputs.   
• Able to explain complex data science concepts in a clear, business-friendly manner.   
• Agile and willing to reprioritise as business needs evolve.  

Knowledge and Skills

Personal Attributes

Core Competencies

Turnaround time

The shortlisting process will only start once the application due date has been reached. The time taken to complete this process will depend on how far you progress and the availability of managers. Deadline to apply 17 June 2026.

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