Require a Data Analyst in Harare, Zimbabwe

Data management: Collect, clean, validate, integrate and maintain claims, membership, contributions, provider and financial datasets. Claims & membership Analytics: Analyze claims frequency, severity, utilization, diagnoses, procedures, high-cost procedures, membership growth, churn, demographics, age profiles. Claims anomaly & fraud detection: Develop rules/models to identify unusual provider, member and claims patterns for investigation.

AI & Automation: Identify opportunities to automate reporting, data analysis, anomaly detection and routine management information. Predictive Analytics: Develop models to predict claims costs, member churn and other material business outcomes. Business process analysis: Identify inefficiencies in claims, membership, authorizations, provider management and other processes and recommend improvements.

Business intelligence: Convert raw data into actionable insights and recommendations for management. Regulatory/ Reporting support: Produce timely and accurate data for regulatory, actuarial, audit and management reporting.

Requirements

Bachelor’s degree in a relevant discipline such as Financial Engineering, Applied Mathematics and Statistics, Actuarial Science, Economics, or a similar qualification from a recognized institution. Risk Management-related professional certification is an added advantage. Minimum of 2-3 years’ experience in business/data analysis, preferably in a medical aid/insurance.

Proficiency in BI tools (Power BI, Tableau, or similar). Experience with statistical tools (R/Python, SPSS, predictive analytics, forecasting, AI/ML). Strong understanding of databases and data management, including Advanced Excel and SQL.