Open Call: African Women in Data Science Fellowship

This timely initiative responds to the growing demand for data-driven leadership to tackle the pressing challenges of food insecurity and climate change across Africa. They invite ambitious African women with foundational experience in data-related work and a strong motivation to deepen their skills and apply data science for transformative impact in agrifood systems and climate resilience.

The Fellowship aims to enhance the leadership and technical capabilities of African women professionals utilizing data science to foster inclusive, evidence-based innovation in agrifood systems and climate resilience. Building on AWARD’s proven track record in cultivating African women leaders in agricultural research and development, the program adapts their Fellowship model to meet the demands of an evolving data and technology landscape.

The program targets African women from Benin, Côte d’Ivoire, Ethiopia, Kenya, and Malawi with demonstrated experience in data-related roles and a commitment to applying data for development. Fellows will be drawn from diverse sectors, including government, academia, research, civil society, development agencies, and the private sector.

Eligible Activities

• Participate in a 7-day, face-to-face women’s leadership course designed to strengthen your confidence, influence, and capacity to lead data-driven solutions (November 2025).
• Join a 2-week immersive in-person data science training course covering Python programming, machine learning, data wrangling, visualization, and statistical analysis (February 2026).
• Complete a 2-month virtual course focused on the application of data science tools to real-world challenges in agrifood systems and climate resilience (April – May 2026).
• Design and implement a data-driven capstone project addressing a practical issue in agriculture or climate. You will receive modest seed funding and technical guidance for project execution (February – September 2026).
• Undertake a competitive short-term institutional placement (1–3 months), known as Advanced Science Training (AST), within your home country. This placement provides an opportunity to apply your skills in a real-world setting and further deepen your technical expertise (May – September 2026).
• Receive ongoing guidance from senior data science professionals through structured mentoring relationships, including orientation, check-ins, and goal setting (March – November 2026).
• Participate in knowledge-sharing sessions, storytelling activities, and professional engagement opportunities through AWARD’s network (Throughout the fellowship).

Eligibility Criteria

• Female citizens of one of the following countries: Benin, Côte d’Ivoire, Ethiopia, Kenya, or Malawi.
• Hold at least a Master’s degree in one of the following: Applied Statistics, Biostatistics, Agricultural Engineering, Biosystems Engineering, Agricultural Economics, Data Science, Bioinformatics or related disciplines.
• Have 5 to 10 years of professional experience in a data-related role, ideally linked to agriculture, climate, or development sectors.
• Demonstrate intermediate proficiency in English (reading, writing, and speaking).
• Be committed to full participation in the 12-month program, including online and inperson activities.
• Resident in an African country throughout the Fellowship period
• Is not a selected Fellow for any other Fellowships offered by AWARD

Pre-Conditions for Participation

• Notification of the Fellowship offer to the successful applicant does not guarantee participation in the Fellowship. Participation will be guaranteed upon the applicant’s:
  • Provision of details of the institution’s head or responsible supervisor who shall endorse their participation in the Fellowship activities
  • Submission of the required documentation (copies of passport and academic certificates) to support the information provided in the application form
  • Acceptance of the AWARD’s code of conduct
  • Timely, official communication to AWARD on their participation in any other capacity-building programs

For more information, visit AWARD.