Chipper is the largest mobile cross-border money transfer platform in Africa. We are a passionate team, dedicated to expanding financial inclusion in some of the global regions most in need of accessible, interoperable, easy-to-use, and affordable financial services.
The Intelligence team is responsible for developing data-driven engineering solutions across domains such as Fraud/Risk, Identity, Product, and Growth. As a key founding member of this team, you will be expected to help shape the team’s culture, best engineering practices, and set direction/focus for tasks and execute them while being a supportive teammate.
We are looking for engineers of generalist stock who don’t tie themselves down to specific languages or frameworks, and are motivated and curious learners that are ready to roll up their sleeves and enjoy solving problems proactively.
Prior experience with machine learning is not needed. Although experience is preferred, we mostly care about a strong willingness to learn.
The New End-to-End Machine Learning Engineer
You will have the rare opportunity to build on top + further enhance a modern ML/Data stack using data powered by emerging NBU (Next Billion Users) in Africa.
The role involves taking data in its rawest form and productionizing solutions using it across the board: from exploratory analysis...to feature engineering…to building and evaluating models over this data… to integrating into Chipper’s products …to building new tooling for our core teams… and more.
In addition to Product, you will also be collaborating with other units in our team, including: Compliance for deeper understanding of risk and fraud, Growth to help find bottlenecks in the on-boarding flow and track the growth of the app through various regional networks, Accounting to scope different financial reporting tasks, and Operations to provide a clear view into the movements of funds through the systems.
Some of the things you can expect to work on include: