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 recruiting to fill the position below:
Job Title: Data Analyst – Credit Eligibility
Location: Lagos (Remote)
Employment Type: Full time
Department: Product Management
Description
- 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.
Responsibilties
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.
- 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.
- 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.
Requirements
Your application should demonstrate:
- Candidates should possess relevant qualifications.
- 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.
- Strong data communication skills — written, oral, and visual.
- Strong interpersonal and collaboration skills.
- (Nice to have) Experience in credit, underwriting, or lending analytics
- 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.
How to Apply
Interested and qualified candidates should:
Click here to apply