About the job
About One Acre Fund
Established in 2006, One Acre Fund empowers over 5.5 million smallholder farmers to enhance productivity and sustainability on their farms. Operating in nine countries that are home to two-thirds of Africa's farmers, we deliver high-quality agricultural inputs, tree seedlings, accessible credit, and comprehensive training programs. This innovative model typically boosts farmers' income and asset growth by over 35% while fostering long-term resilience. Our diverse team of more than 9,000 dedicated professionals plays a crucial role in this mission.
Discover more about our culture and values through our Why Work Here blog post.
About the Role
The Global Data R&D Analyst position offers a unique opportunity to influence decision-making across all facets of One Acre Fund’s program. By leveraging various data types, including sales, yield, demographic, and satellite data, you will help us reach over one million farmers with greater efficiency and impact.
In this role, you will conduct analyses that inform strategic decisions on repayment, program expansion, and operational functions, collaborating closely with program leaders to interpret findings and make informed decisions. You will also play a pivotal role in shaping our data strategy, exploring innovative ways to utilize data to enhance our program outcomes.
Moreover, you will work alongside our robust agronomic and socioeconomic research teams across all operational countries, ensuring that trials are executed to the highest standards. This includes providing analytical support, training for team members, and managing our agronomic data warehouse to facilitate research collaboration, thereby amplifying our impact on smallholder farmers throughout the continent.
To excel in this role, you should possess excellent communication skills and a strong analytical foundation, with experience in experimental design. You should be adept at navigating ambiguous results derived from imperfect data and advising leadership on the risks associated with various decision paths.
This role is intentionally hybrid, requiring proficiency as:
- an experimental methodologist (trial design & causal inference),
- an applied data scientist (production analytics, geospatial methods, modeling), and
- an effective communicator across diverse teams.

