At M-KOPA, you'll own the analytical work that drives our lending strategy. Our Credit Eligibility team operates with a high degree of autonomy — you'll work cross-functionally with engineers, data scientists, growth managers, and commercial stakeholders across multiple countries, bringing analytical rigour to decisions that shape both credit performance and customer outcomes.

M-KOPA’s mission is to make high quality energy affordable to everyone. OUR GROWTH SO FAR... M-KOPA has connected more than 400,000 homes in Kenya,Tanzania and Uganda to solar power with over 550 new homes being added every day.

Your Technical Environment

Languages & tools: Python, SQL, and other analytical tooling

Data: Repayments data, customer behaviour data, third-party data sets

Modelling: Risk modelling and statistical analysis across large, complex data sets

Collaboration: Cross-functional work with engineers, data scientists, analysts, growth managers, and commercial stakeholders

Context: Credit, underwriting, and lending analytics in emerging markets

Our Team Approach

Low-ego, high-impact: We foster a collaborative environment where diversity, innovation, and rigour drive both commercial growth and social impact

Data-driven decision-making: You'll be empowered to make the case for prioritisation and own the analysis that shapes lending strategy

Ownership: You'll have a high degree of ownership over your domain - and the responsibility that comes with it

Ambiguous problems welcome: We look for people who thrive when the problem isn't fully defined yet

Newly established, fast-expanding: You'll be joining at a formative moment for our credit and underwriting capabilities

Qualifications or requirements (e.g., education, skills)

We're looking for someone with experience in roles with significant analytical components who is ready to take real ownership of credit and eligibility decisions at scale.

Experience needed

Required experience:

• Strong statistical modelling and quantitative analysis skills, including the ability to conduct your own analysis of unstructured data
• Experience in credit, underwriting, or lending analytics
• Fluency in Python, SQL, and other relevant analytical tools
• 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

• Analyse M-KOPA's repayments data and other data sources to continuously improve credit scorecards and eligibility criteria while managing credit risk
• Refine loan pricing based on credit analysis and customer behaviour
• Test new loan types to understand customer demand and credit performance
• Monitor credit performance to detect risk shifts and quantify margin impact
• Test the predictiveness of new data sets for eligibility criteria purposes
• Use Python, SQL, and other tools to drive data insights
• Work with data scientists to leverage machine learning models as part of loan eligibility decisions

• Python
• SQL
• Statistical modelling
• Quantitative analysis
• Data analysis
• Credit risk analysis
• Underwriting
• Lending analytics
• Machine learning
• Data communication
• Collaboration

• Strong statistical modelling and quantitative analysis skills
• Experience in credit, underwriting, or lending analytics
• Fluency in Python, SQL, and other relevant analytical tools
• 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