Job Description
M-KOPA is a fast-growing FinTech company offering millions of underbanked customers across Africa access to life-enhancing products and services.
Job Purpose
- In this role, you’ll leadanalysis projects that capture the voices of our customers and agents. Your insights will drive improvements and fuel innovation across the business, making a tangible impact on our services.
What will you do?
- In this role, you’ll dive deep into research data, focusing on both quantitative and qualitative aspects. Using tools like Excel, you’ll clean, interpret, and analyze data to uncover meaningful insights. Whether you’re answering specific business questions or exploring broader trends, your analyses will provide valuable recommendations that drive business decisions.
- Designing clear, user-friendly research reports and dashboards will be a key part of your work. These reports need to summarize results compellingly, drawing out insights and offering actionable recommendations. You’ll also presentyour findings to senior management and other stakeholders, making sure complex data is easy to understand and impactful.
- Managing multiple projectssimultaneously will keep things dynamic. Ensuring data quality through validation checks is essential, and staying updated on the latest trends in data analysis and visualization will help you continually enhance your approach.
- Collaboration is at the heart of what we do. You’ll work cross-functionally with various teams to address important business questions, fostering a culture of data-driven decision-making. Your contributions will support projects across M-KOPA, helping shape our strategic direction.
Expertise
- A bachelor’s degree in a quantitative field, or equivalent experience, will set a strong foundation.
- At least two years of experience in a similar role, along with proficiency in Excel, will be essential.
- You’ll thrive in this role if you have strong written communication skills, experience with BI platforms like Looker or Power BI, and a knack for asking the right questions to structure impactful analysis.