Data Analyst (Life Insurance) at King Price Insurance

Purpose of position:

• Protect, enhance and maintain the organisation’s data environment through strong data quality controls, systems understanding, and the development of robust data and calculation frameworks.

Key Responsibilities

• Own and maintain the integrity of core datasets, ensuring consistent data quality, validation, and governance
• Design, document, and manage calculation frameworks
• Develop BI dashboards and reporting tools that provide reliable management insights, ensuring accuracy and alignment with business rules
• Collaborate closely with actuarial, operations, IT, and finance teams to streamline data flows and documentation
• Structure raw data into clean, auditable, version-controlled frameworks
• Optimise manual processes and develop automated or semi-automated scripts/tools where applicable
• Maintain a strong understanding of system architecture and how various data sources integrate across the organisation
• Support the business with management information, quality monitoring, and operational reporting
• Proactively identify inefficiencies, perform root-cause analysis and propose solutions to improve data processes end-to-end

Requirements

• Matric (essential)
• Tertiary degree in Data Science, Information Systems, Statistics, Mathematics or similar (advantageous)
• 1-4 years’ experience working with data systems, data quality, or BI/reporting environments
• Proficiency in Power BI, SQL, and Excel
• Understanding of data governance, data validation controls, and quality assurance methodologies (advantageous)
• Familiarity with insurance processes and operational data environments (advantageous)

Skills and Attributes

• Exceptional attention to detail and strong analytical capability
• Curiosity-driven and proactive in identifying inefficiencies, risks, and improvements
• Strong problem-solving mindset with the ability to translate business rules into structured logic
• Excellent communication and documentation skills - able to simplify complex data issues for stakeholders
• Strong organisational ability and a commitment to high-quality outputs