Website M-KOPA Solar
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. Each 8W battery powered-system comes with three lights, m… read moreobile phone-charging and a solar powered radio. Customers can now opt for a 20W system with digital TV. As of July 2016, M-KOPA has connected over 400,000 homes to affordable solar power. Current customers will make projected savings of US$ 300 Million over the next four years. M-KOPA’s customers will enjoy 50 million hours of kerosene-free lighting per month. Total employment created in East Africa is 2,500. In March 2016, M-KOPA emerged boldest at Financial Times Arcelor Mittal- Boldness in Business Awards in the Developing Markets category. In February 2016, M-KOPA was recognised as the Best Mobile Innovation for Emerging Markets at the Global Mobile Awards. In 2015, M-KOPA was recognised by Fortune Magazine as one of the Top 50 Companies Changing The World and won the Zayed Energy Future Prize. M-KOPA has also won the 2014 Bloomberg Pioneer Award and 2013 FT/IFC Excellence in Sustainable Finance Award.
What You’ll Do
At M-KOPA, you’ll build and refine the machine learning and credit risk models that power our lending strategy. You’ll sit within a small, high-performing team with end-to-end ownership of credit scoring, loan eligibility, and pricing optimisation — working cross-functionally with engineers, analysts, growth managers, and commercial stakeholders across multiple countries. Join us in combining cutting-edge data science with purpose-driven work that makes digital and financial inclusion possible across Africa.
Day to day, you’ll be:
Building and refining credit scoring and risk modelling solutions that assess customer creditworthiness, default risk, and loan pricing across multiple markets
Developing and testing ML models for loan eligibility and pricing optimisation through A/B testing and statistical analysis
Continuously improving eligibility criteria by analysing repayment data, engineering new features, and monitoring credit performance for risk shifts and margin impact
Collaborating cross-functionally with engineers, data scientists, and commercial stakeholders to scale models into production
Technical Environment
Languages & Libraries: Python, SQL, scikit-learn, pandas, numpy, and relevant ML libraries
Techniques: Predictive modelling, classification/regression, feature engineering, model selection, hyperparameter tuning, A/B testing
Domain: Credit scoring, underwriting, loan pricing, risk analytics
Our Team Approach
Low-ego environment where diversity, innovation, and collaboration drive both commercial growth and social impact
High degree of ownership over your domain — you’re empowered to make data-driven decisions and prioritise solutions
Cross-functional collaboration with engineering, product, and commercial teams across multiple countries
Analytical rigour combined with deep market understanding to serve customers excluded from formal financial services
What You Need
Credit accessibility and affordability are at the core of this role. You’ll join a small, high-performing team where every day brings new modelling challenges and analyses that shape our lending strategy. If building models that can transform financial access for millions of African customers excites you, we’d love to hear from you.
Required Experience:
Experience building predictive models, particularly credit scoring, risk models, or similar classification/regression problems
Strong ML background with hands-on experience in model development, validation, deployment, and performance monitoring
Proficiency in Python, SQL, and relevant ML libraries (scikit-learn, pandas, numpy, etc.) with experience in feature engineering, model selection, and hyperparameter tuning
Experience translating complex model outputs into actionable business strategies and stakeholder communications
Ability to work cross-functionally with product, engineering, and commercial teams
Strong data communication skills — written, oral, and visual
Highly Desirable:
Experience in credit, underwriting, lending analytics, or fintech modelling
Location & Benefits
Fully remote Data Scientist role within UTC -1 to UTC +3 time zones
Work with diverse teams across UK, Europe, and Africa
Professional development programmes and coaching partnerships
Family-friendly policies and flexible working arrangements
Well-being support and career growth opportunities
Apply Through:
jobs.ashbyhq.com
To apply for this job please visit jobs.ashbyhq.com.
