Credit Analyst at M-KOPA

What does day-to-day look like and how do your skills compare?

• Analysis of Digital Financial Services Data – end-to-end analytics workflow that includes defining critical metrics, experimentation, A/B testing, analysis, and building meaningful dashboards.
• Utilising - strong coding skills with Python to work with complex backend data.
• Squads - working closely with our Product and Analytics teams.
• Collaborating - very closely with our Analytics and Machine Learning engineers who are responsible for data orchestration and managing our machine learning models.
• Insights - delivering insightful presentations that help shape commercial decisions in our FinTech group.
• Problem Solving - advising and researching on complex business problems that affect our repayment cycles, staying up to date with industry trends and regulations.