Who are we
There are 2B adults worldwide that don’t have a bank account. 2B. That’s ~40% of the world’s adult population. 350M of these live in Sub Saharan Africa. They are hardworking, young, connected adults that are invisible to the traditional banking system. Fido is changing that. We are building a borderless digital bank so that everyone can access financial products like credit, savings, and payments that make lives easier and better.
Are you tired of building boring enterprise software? Want to be an early employee in a unique consumer brand? Want to do work that has an impact on society? Join us. We build consumer products that are powered by a magical cocktail of real time mission critical ML models, behavioral psychology and financial engineering. We promote meritocracy, decide fast and commit, and worship data. Come join us as one of our early team members.
Join our mission to make financial services accessible and improve the lives of millions of people in Africa and emerging markets.
What you will do
- Develop large scale mission critical machine learning models in finance domains used daily by hundreds of thousands of people.
- Be the end-to-end owner of the model development life cycle - from understanding needs through research and up to productization and evaluation of the model
- Apply cutting edge ML/DL technologies in order to improve our research
- Translate business and product needs into successful scientific and production grade solutions
- Work alongside machine learning experts, big data engineers, product managers and developers from across the organization to solve complex problems
- Provide analysis and insights to support our business growth
Who you are
- 4 + years of hands-on experience as a data scientist in Tech companies.
Working on fraud or Fintech product - advantage
- M.Sc/PHD in a quantitative field (e.g. mathematics, physics, statistics, computer science, economics, natural sciences)
- Strong analytical skills and experience analyzing complex data
- Hands-on experience with toolkits for machine and deep Learning such as TensorFlow/PyTorch/Sklearn
- Comfortable working inside a data team that is built out of data engineers and data analysts
- Experience in working on the entire life cycle of a model
- Experience with python - must
- Experience with creating time series/graph/geo-spatial features and models - advantage
- Knowledge in AWS serving and tools - advantage