Data Analyst
Summary
Data Analyst supporting Telecel Ghana's Telecel Cash mobile money division: building automated dashboards and reports, running deep-dive and predictive analyses of transactions, revenue, and customer behavior to guide commercial decisions. Core stack is SQL, Python/R, and Tableau/Power BI.
Role Purpose
Key Responsibilities
- Generate and disseminate precise, timely, and actionable performance analytics to guide both strategic planning and daily operational choices within the Telecel Cash ecosystem.
- Design, automate, and sustain comprehensive dashboards and reporting frameworks that offer real-time visibility into product metrics, revenue streams, transaction volumes, customer behaviors, merchant activity, and agent performance.
- Execute deep-dive analyses across business segments, products, and customer bases to pinpoint expansion avenues, enhance user engagement, drive product adoption rates, and optimize revenue generation strategies.
- Leverage statistical methods, predictive modeling, and forecasting tools to assist in business planning, profitability evaluations, and scenario-based analysis.
- Collaborate closely with Product, Commercial, Finance, Risk, Technology, and Operations departments to deliver evidence-based recommendations and assess the outcomes of business initiatives, marketing campaigns, and new product launches.
- Uphold rigorous standards for data integrity, ensuring consistency, accuracy, and reliability across all analytical outputs and business intelligence reports.
Requirements
Qualifications
& Experience
- Bachelor's degree
in Statistics, Mathematics, Computer Science, Economics, Finance,
Accounting, Information Systems, or a related quantitative discipline.
- Minimum of 3
years' experience in data analytics, business intelligence, performance
reporting, or commercial analytics.
- Experience within
Mobile Money, Financial Services, Fintech, Telecommunications, or Digital
Payments is highly desirable.
- Strong
understanding of Mobile Money products, customer behavior, transactional
ecosystems, and commercial performance drivers.
Technical
Competencies
- Strong proficiency
in SQL for data extraction, transformation, and analysis.
- Proficiency in
Python, R, or similar analytical programming languages.
- Hands-on
experience with business intelligence and visualization tools, including
Tableau and/or Power BI.
- Strong
understanding of statistical analysis, forecasting, data mining, and
predictive modelling techniques.
- Advanced Microsoft
Excel skills and experience working with large and complex datasets.
- Understanding of
data warehousing concepts, data quality management, and analytics best
practices.