Business Analyst – Credit Eligibility
- Organization
- M-KOPA
- Location
- Remote: London, Lagos, Nairobi, Accra, Kampala, Johannesburg, Cape Town, Kigali
- Job Type
- Full-time
- Where to Apply
- https://www.m-kopa.com/careers#open-roles
We are looking for an 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.”
About Us
We’re building the future of financial inclusion, and data-driven decision making is at the heart of our mission. Our team combines analytical rigor with deep market understanding to develop loan eligibility and pricing for customers who have traditionally been excluded from formal financial services.
We foster a low-ego environment where diversity, innovation, and collaboration drive both commercial growth and social impact. You’ll be empowered to make data-driven decisions and clear cases for prioritization of solutions in a domain that you have a high degree of ownership over.
You’ll be joining a newly established team that’s rapidly expanding our credit and underwriting capabilities. We are looking for someone who loves analyzing complex data and solving challenging, ambiguous data problems — if that sounds like you, you might be a fit!
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
