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Position Title: Data Analytics Intern
Location: Lusaka, Zambia
Reports to: Data Analyst
Position Overview: The Data Intern will support the Data Analyst with the collection, cleaning, validation, mapping, and documentation of data used for reporting, portfolio analysis, and catastrophe modelling. The role will focus particularly on improving the completeness and usability of underwriting exposure data. This is a practical development role suited to a recent graduate who is detail-oriented, comfortable working with structured data, and interested in building experience within the insurance and reinsurance industry. The intern will work under close supervision and will assist with recurring and ad hoc data activities across the business.
Key Responsibilities:
1. Exposure Data Collection and Mapping: Extract and consolidate relevant exposure information from underwriting files, slips, schedules, and supporting documentation. Capture and update approved data fields in the relevant internal tools and systems. Map policy and risk attributes required for detailed analytics.
2. Data Quality and Validation: Review datasets for completeness, consistency, duplication, and obvious data errors before they are used for reporting or modelling. Maintain clear records of missing information, assumptions, outstanding queries, and data corrections. Support the Data Analyst in following up data gaps with Underwriting, Claims, and other relevant departments. Apply approved naming conventions, data standards, and confidentiality requirements when handling company information.
3. Catastrophe Modelling and Event Readiness: Assist in preparing, formatting, and validating exposure datasets for catastrophe modelling exercises and external modelling platforms. Support the maintenance of event watchlists and at-risk policy listings during natural catastrophe and geopolitical events. Assist with the preparation of rapid exposure reports within required turnaround times, under the direction of the Data Analyst.
4. Reporting and Basic Analytics Support: Assist with recurring data preparation and reporting activities using Excel, Power Query, Power BI, or other approved tools. Prepare simple summaries, reconciliations, charts, and data extracts for review by the Data Analyst. Support ad hoc data requests and portfolio reviews from Underwriting, Claims, Actuarial, Finance, and Management.
5. Documentation, Collaboration and Development: Document data sources, mapping rules, validation steps, and recurring processes in a clear and consistent manner. Work closely with the Data Analyst and cooperate with business teams to obtain and clarify required information. Participate in relevant training and progressively build knowledge of reinsurance data, systems, reporting and analytical practices. Perform other reasonable data-related duties assigned by the Data Analyst or Head of Data, Analytics and Technology.
Key Competencies: Strong attention to detail and commitment to data accuracy. Basic analytical and problem-solving ability. Good working knowledge of Microsoft Excel, including formulas, filters, and data organization. Ability to follow instructions, work methodically, and meet agreed deadlines. Clear written and verbal communication skills. Ability to maintain confidentiality and handle business information responsibly. Willingness to learn, receive feedback, and work collaboratively with others.
Qualifications and Experience: Recent graduate or final-year student in Data Science, Statistics, Computer Science, Information Systems, Actuarial Science, Mathematics, Economics, Finance, Business Analytics, or a related field. Basic practical experience working with spreadsheets and structured data through academic, internship, project, or volunteer work. Exposure to Power BI, Power Query, SQL, or Python will be an advantage. Prior experience in insurance, reinsurance, financial services, research, data entry, or data quality work will be an advantage. No full-time work experience is required; evidence of initiative, reliability, and willingness to develop is important.
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