About Company
Econet Wireless Zimbabwe is a leading diversified telecommunications group with operations and investments across Africa. As a pioneer in providing innovative digital solutions, Econet has transformed the lives of millions by offering mobile, internet, and payment services, among others. With a steadfast commitment to connectivity and community development, Econet drives technological advancement and economic empowerment throughout Zimbabwe. Joining Econet means becoming part of an ambitious team dedicated to excellence, innovation, and making a tangible impact on the future of telecommunications and digital services. Our culture fosters growth, collaboration, and continuous learning, providing a robust platform for professionals to thrive and contribute to a truly connected Africa. We are at the forefront of digital transformation, constantly seeking new ways to enhance our customer experience and operational efficiency through data-driven strategies.
Job Description
Econet Wireless Zimbabwe is seeking an accomplished and highly motivated Experienced Data Analyst to join our dynamic Business Intelligence team in Harare. In this pivotal role, you will be instrumental in transforming complex data sets into actionable insights that drive strategic decisions across various business units. You will leverage your expertise in data analysis, statistical modeling, and visualization to uncover trends, predict outcomes, and provide comprehensive reports that inform product development, marketing strategies, operational efficiencies, and customer experience enhancements. This is an exciting opportunity for a professional who is passionate about data storytelling, possesses a keen eye for detail, and thrives in a fast-paced, innovative environment within the telecommunications sector. As an Experienced Data Analyst, you will not just process numbers; you will be the architect of understanding, enabling our leadership to make informed choices that shape the future of connectivity in Zimbabwe.
Your core mission will be to translate complex business questions into robust analytical problems, designing and implementing data-driven solutions that directly contribute to our bottom line and customer satisfaction. You will collaborate closely with cross-functional teams including marketing, product development, finance, and operations, acting as a critical bridge between raw data and strategic business intelligence. This role demands a proactive individual who can champion data best practices, identify opportunities for data integration and automation, and continuously seek out new tools and methodologies to enhance our analytical capabilities. If you are a curious, analytical mind eager to make a significant impact in a leading telecommunications company, we encourage you to apply and help us build a more connected future.
Key Responsibilities
- Design, develop, and maintain scalable data models, dashboards, and reports using various BI tools to visualize key performance indicators (KPIs) and business trends.
- Perform in-depth statistical analysis on large, complex datasets to identify patterns, anomalies, and underlying causes of business performance.
- Collaborate with stakeholders across departments to understand business requirements, define analytical objectives, and deliver insights that support strategic decision-making.
- Develop and implement robust data extraction, transformation, and loading (ETL) processes to ensure data integrity and accessibility.
- Conduct ad-hoc analysis and deep dives into specific business problems, presenting findings clearly and concisely to both technical and non-technical audiences.
- Identify opportunities for data collection and process improvements, working with data engineering teams to enhance data infrastructure.
- Contribute to the development of predictive models and machine learning applications to forecast trends and optimize business operations.
- Mentor junior data analysts, fostering a culture of continuous learning and data excellence within the team.
- Stay abreast of industry best practices, new technologies, and emerging trends in data analysis, business intelligence, and telecommunications.
Required Skills
- Bachelor's degree in Computer Science, Statistics, Mathematics, Economics, or a related quantitative field.
- Minimum 3 years of hands-on experience as a Data Analyst or in a similar analytical role.
- Proficiency in SQL for data querying and manipulation.
- Strong experience with data visualization tools such as Tableau, Power BI, or Qlik Sense.
- Expertise in statistical analysis and advanced Excel for data modeling and reporting.
- Proven ability to work with large datasets and translate complex data into actionable business insights.
- Excellent communication and presentation skills, with the ability to convey complex analytical concepts to diverse audiences.
- Demonstrated problem-solving skills and attention to detail.
Preferred Qualifications
- Master’s degree in a quantitative field.
- Experience with programming languages such as Python or R for data analysis and statistical modeling.
- Familiarity with cloud data platforms (e.g., AWS, Azure, GCP) and big data technologies (e.g., Spark, Hadoop).
- Experience in the telecommunications industry or a related data-intensive sector.
- Knowledge of machine learning concepts and their application in business scenarios.
- Project management skills and experience leading analytical projects.
Perks & Benefits
- Competitive salary package and performance-based bonuses.
- Comprehensive health and wellness benefits.
- Opportunities for professional development and continuous learning.
- Dynamic and collaborative work environment.
- Access to cutting-edge technologies and innovative projects.
- Employee wellness programs and initiatives.
- Paid time off and holidays.
How to Apply
Interested and qualified candidates are encouraged to apply by clicking on the application link below. Please ensure your CV and cover letter highlight your relevant experience and qualifications for this role. Only shortlisted candidates will be contacted.