M-KOPA is a fast-growing FinTech company offering millions of underbanked customers across Africa access to life-enhancing products and services. From our roots as the pioneer in pay-as-you-go �PayGo� solar energy for off-grid homes, we have grown into one of the most advanced connected asset financing platforms in the world, empowering a broad range of customers to achieve progress in their lives.
- We are looking for a Product/Business Data Analyst to help drive M-KOPA’s mission of building transformative lifetime financial partnerships with our customers.
- ''This role offers the opportunity to directly impact millions of customers' access to credit by building underwriting frameworks. You will be a member of a small team with the big responsibility of continuously improving M-KOPA’s loan offers and eligibility criteria in order to drive growth while managing credit losses and margins. You'll work cross-functionally with engineers, data scientists, other analysts, growth managers, and commercial stakeholders across multiple countries.''
In this role, you would be responsible for:
- Analyzing M-KOPA's repayments data and other data sources to continuously improve our loan eligibility criteria while managing credit risk
- Refining loan pricing based on credit analysis and customer behavior
- Testing new types of loans to understand customer demand and credit performance
- Monitoring credit performance to detect risk shifts and quantify margin impact
- Testing the predictiveness of new data sets for the purposes of eligibility criteria
- Using Python, SQL, and other tools for data analysis to drive insights
- Working with data scientists to leverage machine learning models as part of loan eligibility decisions
This role can be remote or hybrid, but candidates must be located within our time zones (UTC -1 to UTC+3) to ensure effective collaboration with teams across our multiple locations.
Your application should demonstrate:
- Several years in roles with significant analytical components
- Strong statistical modeling and quantitative analysis skills, including the ability to conduct your own analysis of unstructured data
- Fluency in Python, SQL, and other relevant tools for data analysis
- Experience translating complex data insights into actionable business strategies
- Ability to work cross-functionally with product, engineering, and commercial teams
- Strong data communication skills — written, oral, and visual
- Strong interpersonal and collaboration skills
- (Nice to have) Experience in credit, underwriting, or lending analytics
Method of Application
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