Data Analyst

About the Role

What will you do?

Responsibilities

• To produce reliable business information and actionable insights through the collation, validation and analysis of data, enabling informed underwriting, pricing, claims and portfolio management decisions within the CAHTMAEB business cluster.
• Produce and analyse portfolio reports covering premiums, claims, loss ratios, rate movements and other relevant performance indicators.
• Identify emerging trends, underwriting opportunities, claims latency, risk concentrations and data anomalies.
• Translate analytical findings into clear recommendations that support risk selection, pricing, underwriting actions and product reviews.
• Monitor exposure accumulations, concentration risks and applicable limit breaches.
• Develop and maintain reliable datasets for reporting, pricing and modelling.
• Perform regular data validation, reconciliation and quality testing.
• Identify root causes of data quality issues and work with relevant stakeholders to implement sustainable corrective actions.
• Maintain data definitions, business rules, process documentation and appropriate audit trails.
• Produce accurate and timely management information, portfolio reports and dashboards.
• Develop and maintain self-service reports and business intelligence solutions.
• Ensure that reports use consistent definitions, approved data sources and appropriate controls.
• Present complex findings clearly to technical and non-technical stakeholders.
• Prepare and validate data for pricing, segmentation, forecasting and predictive modelling.
• Support the testing, implementation and monitoring of rates, underwriting rules and analytical models.
• Assist with system changes, data migrations, rate updates and user acceptance testing.
• Support exposure analysis and reinsurance treaty renewals, regulatory and governance reporting.
• Work with underwriting, actuarial, claims, reinsurance, finance and technology teams to deliver practical data solutions.
• Automate repeatable data and reporting processes to reduce manual effort and operational risk.
• Respond to ad hoc analytical requests and data enquiries.
• Promote data standards and support users in adopting reports, dashboards and analytical tools.
• Participate in approved AI and automation initiatives, including testing, implementation and monitoring.
• Contribute to the development, deployment and responsible governance of data and AI solutions that improve decision making, operational efficiency and customer outcomes.
• Work with business and technology stakeholders to identify and prioritise AI use cases that support Santam’s strategic objectives, competitive advantage and long-term business performance.
• Support the ongoing monitoring of AI solutions for performance, data quality, explainability, fairness and compliance with approved governance, risk and ethical standards.

Requirements

• Bachelor’s degree in Mathematics, Statistics, Actuarial Science, Data Science, Computer Science, Economics or another relevant quantitative discipline
• At least two years’ relevant experience in data analysis, business intelligence, actuarial analysis, pricing analytics or a similar analytical role
• Experience extracting, reconciling and analysing data from multiple sources
• Experience developing reports or dashboards for business users
• Experience in short-term insurance, commercial insurance or casualty insurance
• Exposure to underwriting, pricing, claims, exposure management or reinsurance data
• Experience working with policy administration systems and data warehouses
• Advanced Excel, including data validation, reconciliation and analytical modelling
• Proficiency in SQL for data extraction, transformation and analysis
• Experience using a business intelligence and visualisation tool, preferably Power BI
• Strong data management and data quality skills
• Experience working with relational databases, data warehouses or similar analytical data environments
• Ability to translate business requirements into clear analytical outputs
• Understanding of the AI solution lifecycle, including use case identification, data preparation, testing, deployment, performance monitoring and governance.
• Ability to evaluate AI generated outputs critically and translate them into reliable, explainable and actionable business insights.
• Awareness of responsible AI principles, including data privacy, security, fairness, transparency, human oversight and model risk.
• Experience using AI enabled analytical, automation or productivity tools in a controlled business environment.
• Experience contributing to or driving the development, implementation and ongoing monitoring of machine learning, generative AI or other advanced analytical solutions.
• Experience with Python, R or another analytical programming language
• Knowledge of statistical modelling, forecasting, segmentation or machine learning
• Familiarity with insurance policy, claims, pricing and exposure data
• Collaboration
• Business and stakeholder focus
• Results orientation
• Analytical thinking
• Attention to detail
• Innovation and continuous improvement
• Adaptability
• Effective communication
• Planning and organisation
• Relationship building
• Data extraction, manipulation and reconciliation
• Database and data-warehouse concepts
• Business intelligence and visualisation
• Statistical analysis and modelling
• Reporting automation
• Data quality management
• Systems integration and user acceptance testing
• Insurance portfolio analysis