There are 2 billion adults worldwide who don’t have a bank account. That’s close to 40% of the world’s adult population. 350 million of them live in Sub-Saharan Africa. They are hardworking, young, connected adults that lack access to the traditional banking system. Fido is changing that. We are empowering individuals and entrepreneurs to take advantage of opportunities in Africa.

The latest innovation from Fido called Fido Score will shift power back to the people by empowering them to build and maintain a digital financial track record.

We build consumer products powered by a magical cocktail of real-time mission-critical machine-learning models, behavioral psychology, and financial engineering. We promote meritocracy, act quickly, commit, and worship data.

Ready for your next career move?

Are you sharp, motivated, and purpose-driven? We are looking for you

Join us in our mission to make financial services accessible in Africa.

What you will do

• Be the end-to-end owner of the model development life cycle - from understanding business needs through research and up to productization and monitoring.
• Apply cutting edge ML/DL technologies to solve actual business problems that will be an invaluable part of Fido product.
• Work in a highly professional multidisciplinary group of Data Scientists, Data Engineers and Data Analysts.
• Work with diverse data types (tabular, visual, textual, time-series, geo-spatial, graphs, and more) to create models in the finance, risk management, recovery and fraud domains.

Who you are

• 3 + years of hands-on experience as a data scientist in tech companies.
• M.Sc in a quantitative field (Computer Science \ Engineering \ Mathematics \ Statistics or similar) with focus on applied statistics, AI, machine learning, or related fields.
• Proven record of translating business and product needs into successful scientific and production grade solutions.
• Strong analytical skills and experience analyzing complex data.
• Team player with strong communication skills.
• High proficiency in python.
• Hands-on experience with machine learning & deep learning frameworks such as Sklearn and Pytorch or Tensorflow.
• Knowledge in AWS serving and tools - advantage.
• Vision and NLP experience - advantage.
• Experience with LLMs - advantage.