Research Scientist - Financial Inclusion

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M-KOPA

πŸ“Remote - United Kingdom

Summary

Join M-KOPA's Data Science Team as a Research Scientist and contribute to expanding financial inclusion across Africa. Your algorithms will directly impact millions by unlocking financial opportunities for the underbanked. You will build and prototype generative AI models for credit risk assessment and customer behavior modeling, publishing your research at top conferences. Collaborate with teams across Africa and Europe to deploy machine learning solutions. This role offers research freedom, immediate impact, and global recognition within a mission-driven company.

Requirements

  • Hands-on experience or Academic Publication in generative models (VAEs, GANs, diffusion models, or related methods)
  • Advanced expertise in mathematics, statistics, and theoretical computer science
  • Experience with deep learning, reinforcement learning, or specialised Machine Learning domains
  • Experience with structured or unstructured data
  • Proven ability to translate research into scalable algorithms

Responsibilities

  • Build generative AI models (VAEs, GANs, diffusion models) for financial inclusion across Africa
  • Prototype and iterate advanced models, from credit risk assessment to customer behaviour modeling
  • Publish research at top conferences (NeurIPS, ICML, ICLR, AAAI etc) while solving real-world problems
  • Work with teams across Africa and Europe to deploy Machine Learning solutions that expand financial access

Preferred Qualifications

Ideally a publication record in Machine Learning research (NeurIPS, ICML, ICLR, AAAI etc preferred)

Benefits

  • This is a fully remote role , you would be working within the following time zone (UTC -1 / UTC+3) with a diverse group of other employees working remotely from locations such as UK, Europe and Africa
  • At M-KOPA, we empower our people to own their careers through diverse development programs, coaching partnerships, and on-the-job training
  • We support individual journeys with family-friendly policies, prioritize well-being, and embrace flexibility

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