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

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