Finance Transformation Manager — M-KOPA

Finance Transformation Manager - ( Finance Engineering & AI) - M-KOPA

(This is not a traditional Finance Transformation role. We're looking for a technical builder who wants to apply engineering, automation, data and AI to finance.)

You've built systems, automated processes, solved technical problems, or turned complex data into something that works better.

Now imagine applying that thinking to finance.

We're looking for someone who sees reconciliation, reporting, planning, data and financial systems as problems to engineer , not simply processes to manage.

You might come from software engineering, data, automation, consulting, ERP, fintech or another technical environment. You don't need to have spent your career in Finance. What matters is that you've built something real, solved a real problem and can show us how you did it.

We'd rather hire a strong technical builder who can learn Finance than a traditional finance professional who has never built anything.

Where this sits

M-KOPA is one of Africa's fastest-growing fintechs, now serving 7 million customers across five markets and having unlocked over $2 billion in credit .

Our Finance function runs on Microsoft Dynamics and Anaplan, increasingly supported by AI tools such as Claude, and we're reaching a point where the opportunity is bigger than simply improving existing processes.

We need to make our finance infrastructure more intelligent, automated, reliable and scalable .

That's where you come in.

You'll sit inside Finance, but operate with an engineering mindset — understanding how our systems, data, processes and controls fit together, identifying where they break down, and building better ways of working.

Why now?

We've grown from 5 million customers to 7 million, with 10 million next in view.

That scale creates increasingly complex challenges across reconciliation, reporting, planning, data integrity, systems integration and financial operations.

We don't want to solve those challenges by simply adding more people to existing processes.

We want to engineer the processes differently .

If a reconciliation takes two days, your instinct should be to ask:

Why does it take two days? What data is missing? What can be integrated? What can be automated? What can be validated automatically? What should a person actually be doing?

If Dynamics and Anaplan produce different numbers, you shouldn't be satisfied with identifying the variance. You should want to understand the underlying data flow, identify the root cause and help fix the system.

If reporting requires repeated manual intervention, you should be thinking about how to redesign the workflow.

And if AI can remove hours of repetitive work, you should be asking how to deploy it safely and effectively — with the right controls and human oversight.

What makes this different