Product Analyst

November 12

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M-KOPA

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Founded in 2011, M-KOPA is a fintech platform that provides digital financial services to underbanked consumers by leveraging data to combine digital micropayments with the Internet of Things [IoT] technology. With operations in Kenya, Uganda, Nigeria and Ghana, M-KOPA’s platform has provided over $1 billion in credit and enabled 3 million customers to access smartphones, electric motorcycles, solar power systems, digital loans and health insurance. The company directly employs nearly 2,000 people across Africa and has created over 10,000 roles for sales agents since the start of 2020.

1001 - 5000 employees

📋 Description

• 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

🎯 Requirements

• Several years in roles with significant analytical components • Strong statistical modeling and quantitative analysis skills, including the ability to conduct your own analysis of unstructured data • Fluency in Python, SQL, and other relevant tools for data analysis • 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 • (Nice to have) Experience in credit, underwriting, or lending analytics

🏖️ Benefits

• Family-friendly policies • Professional development opportunities • Company culture prioritizing well-being • Flexible working hours