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Senior Data Scientist - Credit Modeling at M-KOPA Solar

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Company Details
Industry: Electrical/Electronic Manufacturing
Description: 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, mobile 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 5
Job Description

In this role, you would be responsible for:

  • Building and refining credit scoring models to assess customer creditworthiness and default risk
  • Analyzing M-KOPA’s repayments data and other data sources to continuously improve our loan eligibility criteria while managing credit risk
  • Developing machine learning models for loan eligibility decisions and pricing optimization
  • Refining loan pricing based on credit analysis, predictive modeling, and customer behavior
  • Testing new types of loans to understand customer demand and credit performance through A/B testing and statistical analysis
  • Monitoring credit performance to detect risk shifts and quantify margin impact using advanced analytics
  • Testing the predictiveness of new data sets and feature engineering for enhanced model performance
  • Using Python, SQL, and other tools for data analysis and model development
  • Collaborating with data scientists to implement and scale machine learning models in production

This role can be remote or hybrid, but candidates must be located within our time zones (UTC -1 to UTC+3) to ensure effective collaboration with teams across our multiple locations.

Your application should demonstrate:

  • Several years of experience building predictive models, particularly credit scoring, risk models, or similar classification/regression problems
  • Strong machine learning background with experience in model development, validation, and deployment
  • Advanced statistical modeling and quantitative analysis skills, including experience with model evaluation metrics and performance monitoring
  • Proficiency in Python, SQL, and relevant ML libraries (scikit-learn, pandas, numpy, etc.)
  • Experience with 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
  • Strong interpersonal and collaboration skills
  • (Highly desirable) Experience in credit, underwriting, lending analytics, or fintech modeling
Salary: Discuss During Interview
Education: Diploma
Employment Type: Full Time

Key Skills

data  informationtechnology 
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