WE ARE LOOKING FOR AN ELIGIBILITY PRODUCT ANALYST TO HELP DRIVE M-KOPA’S MISSION OF BUILDING TRANSFORMATIVE LIFETIME FINANCIAL PARTNERSHIPS WITH OUR CUSTOMERS.

This role offers the opportunity to drive significant customer and business impact. 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 foster a low-ego environment where diversity, innovation, and collaboration drive both commercial growth and social impact. Our team values psychological safety and takes a discovery-first approach to problem solving. 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.
We are looking for someone who loves analyzing complex data and solving challenging, ambiguous data problems — if that sounds fun to you, you might be a fit!
Working on a team, you will determine M-KOPA’s loan eligibility criteria and develop our loan offers and pricing, to ensure that we are offering loans that customers want and can afford while also achieving our business growth objectives.
This is a fully remote role, you would be working within the following time zone (UTC -1 / UTC+3) with a diverse group of other employees working remotely from locations such as UK, Europe and Africa.

• Analyzing M-KOPA’s repayments data and other data to continuously improve our loan eligibility criteria
• Developing new loan offers and pricing based on customer demand and credit analysis
• Monitoring the credit performance of your loans to identify where we need to adjust eligibility criteria and/or pricing
• Testing the predictiveness of new data sets for the purposes of eligibility criteria
• Testing new types of loans to understand customer demand and credit performance
• Working with engineers to implement changes to our eligibility criteria
• Working with data scientists to leverage machine learning models as part of loan eligibility decisions