Data Scientist

Who we are

Fido empowers millions across Africa to take control of their finances with ease. As a leader in cutting-edge financial technology,

Fido clears the way for building credit, securing instant loans, making smart investments, and obtaining tailored insurance. No banker’s hours, no hidden fees – just endless opportunities.

From city centers to rural communities, Fido is breaking barriers and creating financial freedom, providing access to innovative tools and services that foster growth and empowerment. By leveraging advanced technology,

Fido is shaping a future of opportunity and financial inclusion across the continent.

Join the team and be a part of leading this transformative change, driving impact where it matters most.

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.
  
  

• 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.
• Strong Engineering Orientation: You are a builder who writes clean, production-ready code, not just research scripts.
• 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.
• Generative AI: Hands-on experience with the Modern LLM stack (e.g., RAG, LangChain, fine-tuning open-source models, and prompt engineering)