Vacancy title:
Data Scientist – Commercial Insights

[Type: FULL_TIME, Industry: Financial Services, Category: Computer & IT]

Jobs at:
M-KOPA Solar

Deadline of this Job:
Thursday, June 12 2025

Duty Station:
Nairobi | Nairobi | Kenya

Summary
Date Posted: Friday, May 23 2025, Base Salary: Not Disclosed

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JOB DETAILS:

Job Description

M-KOPA’s mission is to make high quality energy affordable to everyone. OUR GROWTH SO FAR… M-KOPA has connected more than 400,000 homes in Kenya,Tanzania and Uganda to solar power with over 550 new homes being added every day.

Data Scientist – Commercial Insights

• We are looking for a Data Scientist – Commercial Insights to join our Data Science Team as we scale up and drive digital and financial inclusion across our markets.
• • Each day will bring intellectually stimulating challenges that stretch your scientific capabilities:
  • You’ll conduct applied machine learning research and develop innovative algorithms to solve complex, real-world problems. From credit risk assessment to customer behaviour modelling, your work will tackle sophisticated challenges with substantial business and social implications.
  • You’ll prototype, test, and iterate advanced models, integrating state-of-the-art academic insights into practical solutions. This process will allow you to bridge the gap between theoretical possibilities and implementable algorithms.
  • As a key member of our central Data Science team, you’ll actively engage with academic institutions to accelerate innovation and maintain M-KOPA’s competitive advantage. These collaborations will keep your research at the cutting edge while fostering relationships with the broader scientific community.
  • Throughout your work, you’ll balance theoretical exploration with practical application, ensuring your research delivers both scientific advancement and tangible business impact.

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  Must-Have Qualifications:

  • Advanced expertise in machine learning, mathematics, statistics, and theoretical computer science.
  • Experience or academic publication in generative modelling (e.g., VAEs, GANs, diffusion models, or related methods)
  • Strong publication record in prestigious conferences (NeurIPS, ICML, ICLR)
  • Proven ability to translate academic research into practical, impactful algorithms
  • Experience with deep learning, reinforcement learning, or other specialized machine learning domains
  • Exceptional analytical, critical thinking, and problem-solving abilities

Work Hours: 8

Experience in Months: 12

Level of Education: bachelor degree

Job application procedure

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