Data Scientist, ICT Administration Office at Aga Khan University Hospital

Aga Khan University

  • Nairobi
  • Permanent
  • Full-time
  • 1 day ago
Job Purpose/Summary
  • AKU is building an AI-enabled product to address the challenges of low- and middle-income countries (LMICs). As part of the
(CDIO), you will work at the intersection of data science, AI, and product development to shape and deliver high-impact GenAI tools. * We are seeking a Data Scientist / Analyst who brings strong technical skills in machine learning and NLP, and is eager to take on full stack development responsibilities. You will work closely with engineering and academic teams, and design stakeholders to co-develop product features, define data workflows, and deploy AI-enabled tools that serve both academic excellence and social development.Key Roles and Responsibilities
  • Design, train, evaluate, and refine LLM-based workflows and data pipelines.
  • Define features, user stories, and manage backlog. Coordinate agile sprints.
  • Ensure training and inference datasets are complete, accurate, and relevant.
  • Engage with domain experts, faculty, and operations teams to gather feedback.
  • Conduct A/B testing, collect usability feedback, optimize UX in GenAI outputs.
  • Document data lineage, model decisions, and ensure privacy and security.
  • Publish learnings, contribute to internal workshops, stay current in GenAI.
Relevant Experience and Qualifications
  • BSc or MSc in Data Science, Computer Science, Engineering, or a related quantitative field.
  • A proven track record in building and shipping successful analytics software products at scale at a high-growth, high-tech company.
  • 2+ years of experience in a data science or engineering role.
  • Experience with GenAI or NLP techniques (e.g., transformers, prompt engineering).
  • Background in building data-driven products using agile methodologies.
  • Proficient in Python, SQL, ML libraries (scikit-learn, Transformers, LangChain, etc.)
  • Familiarity with BI tools (e.g., Power BI), and data versioning / MLOps pipelines.
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