Data Analyst

Role Overview

This position focuses on providing insightful, data-driven intelligence essential for the growth, financial performance, and operational effectiveness of Telecel Cash. The role requires transforming complex datasets into strategic insights that support performance monitoring, forecasting, and reporting, enabling leadership to make informed decisions and meet crucial business goals.

Key Responsibilities

• Produce and distribute accurate, timely analytics to support strategic planning and day-to-day operations within the Telecel Cash platform.
• Create, automate, and maintain detailed dashboards and reports to offer real-time data on product metrics, revenues, transactions, customer and merchant behavior, and agent performance.
• Conduct comprehensive data analyses across business units and customer segments to identify new growth opportunities, improve user engagement, and enhance revenue strategies.
• Apply statistical approaches, predictive analytics, and forecasting models to inform business planning and profitability assessments.
• Work collaboratively with Product, Commercial, Finance, Risk, Technology, and Operations teams to deliver data-backed recommendations and evaluate the impact of initiatives and campaigns.
• Ensure data accuracy, consistency, and reliability across all analytical outputs and business intelligence reports.

Qualifications and Experience

• Bachelor's degree in relevant quantitative fields such as Statistics, Mathematics, Computer Science, Economics, Finance, Accounting, or Information Systems.
• At least 3 years of experience in data analytics, business intelligence, performance reporting, or commercial analytics.
• Experience in sectors including Mobile Money, Financial Services, Fintech, Telecommunications, or Digital Payments is highly valued.
• Strong knowledge of Mobile Money products and transactional ecosystems, plus insight into commercial performance drivers.

Technical Skills

• Advanced proficiency with SQL for data extraction and manipulation.
• Proficient in analytical programming languages such as Python or R.
• Experienced with business intelligence and visualization platforms like Tableau and Power BI.
• Strong foundation in statistical analysis, forecasting, data mining, and predictive modeling techniques.
• Expertise in Microsoft Excel handling complex and large datasets.
• Understanding of data warehousing principles, data quality management, and analytics best practices.