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.

Vereiste vaardigheden

Data cleaning and validationData integration and ETL (dataset merging, joining, ingestion)SQLAdvanced ExcelBI tools (Power BI, Tableau or similar)Statistical programming (R or Python)Predictive analytics and modeling (claims cost, churn forecasting)Anomaly and fraud detection (rules and model development)Claims analytics (frequency, severity, utilization, diagnoses, procedures)Membership analytics (churn analysis, demographics, age profiling)AI and automation for reporting and routine analysisBusiness intelligence and insight generation (convert raw data to recommendations)Regulatory, actuarial and audit reporting supportBusiness process analysis and improvement (claims, membership, authorizations)Risk management familiarity or certification (advantage)

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