About One Acre Fund

Founded in 2006, One Acre Fund equips 5.5 million smallholder farmers to make their farms more productive. Across nine countries that together are home to two-thirds of Africa's farmers, we provide high-quality farm supplies, tree seedlings, accessible credit, modern agronomic training, and a wide range of other agricultural services. On average, this model enables any farmer to increase their income and assets on supported land by more than 35 percent, while permanently improving their resilience. This is all made possible by our team of 9,000+ full-time staff, drawn from diverse backgrounds and professions. To learn more, please see our Why Work Here blog post.

Our Rwanda program, founded in 2007 is our largest and operates under the local brand Tubura. We have more than 3,000 staff across all four provinces of Rwanda, as well as in Kigali. Together, we served more than 2.8 million farmers in 2024. We work closely with the government to support national efforts to improve food security. Additionally, we help channel funding and resources to promising agri-SMEs, supporting farmers by providing a market for high-impact crops such as coffee, avocado, and chili.

About the Role

Seeking an exceptional data analytics professional to advise the organization on new products and practices that can generate "farmer impact" utilizing big data (longitudinal datasets and meta-analyses) from several sources.

Responsibilities

• Advanced Trial & Tricot Analytics: Lead statistical and machine-learning analyses of multi-season trial and Tricot datasets to evaluate performance, identify drivers of outcomes, and generate actionable recommendations.
• Geospatial & Segmentation Analysis: Apply GIS and spatial analytics to stratification, yield gap mapping, zoning, and farmer segmentation to define recommendation domains.
• Data Infrastructure & Automation: Design, maintain, and continuously improve the INN data warehouse and automated data pipelines across trials, weather, and geospatial datasets.
• Dashboards & Visualization: Develop and maintain interactive dashboards and visual tools, working closely with Research Specialists to ensure robust data integration and usability.
• Weather & Environmental Data: Oversee weather data systems, ensure data quality, and integrate derived indices into trial and spatial analyses.
• Data Coordination & Integration: Manage the acquisition, integration, and quality of data from internal teams and external partners.
• Reporting & Insight Translation: Deliver clear, decision-ready reports and visualizations, translating complex analyses into insights for research, management, and scaling partners.
• People Management & Capability Building: Lead and mentor the data team, supporting performance, professional growth, and strong analytical capability across the department.

Career Growth and Development

We have a strong culture of constant learning and we invest in developing our people. You’ll have weekly check-ins with your manager, access to mentorship and training programs, and regular feedback on your performance. We hold career reviews every six months, and set aside time to discuss your aspirations and career goals. You’ll have the opportunity to shape a growing organization and build a rewarding long-term career.

Qualifications

Across all roles, these are the general qualifications we look for. For this role specifically, you will have:

• Bachelor’s degree in Data Science, Statistics, Agronomy, or a related field.
• Strong grounding in statistics and machine learning applied to real-world agricultural problems.
• Experience with geospatial analysis, GIS tools, and remote sensing for agricultural insights.
• Proficient in Python/R, SQL, and modern data infrastructure and visualization tools.
• Ability to translate complex data into clear insights for technical and non-technical audiences.
• Demonstrated understanding of agronomic concepts, sampling methods, and data quality best practices.
• Strong problem-solving skills with high attention to detail and data integrity.
• Experience collaborating, mentoring, or leading analytics projects is an added advantage.

Preferred Start Date

As soon as possible

Job Location

Kigali, Rwanda

Benefits

Health insurance, housing, and comprehensive benefits

Contract Duration

2 Years

Eligibility

One Acre Fund can support a work permit for this role. However, nationals of (or those with an extensive professional background and work history in) our countries of operation are preferred.

• Lead statistical and machine-learning analyses of multi-season trial and Tricot datasets to evaluate performance, identify drivers of outcomes, and generate actionable recommendations.
• Apply GIS and spatial analytics to stratification, yield gap mapping, zoning, and farmer segmentation to define recommendation domains.
• Design, maintain, and continuously improve the INN data warehouse and automated data pipelines across trials, weather, and geospatial datasets.
• Develop and maintain interactive dashboards and visual tools, working closely with Research Specialists to ensure robust data integration and usability.
• Oversee weather data systems, ensure data quality, and integrate derived indices into trial and spatial analyses.
• Manage the acquisition, integration, and quality of data from internal teams and external partners.
• Deliver clear, decision-ready reports and visualizations, translating complex analyses into insights for research, management, and scaling partners.
• Lead and mentor the data team, supporting performance, professional growth, and strong analytical capability across the department.

• Statistical and machine learning analysis
• Geospatial analysis, GIS tools, and remote sensing
• Python/R, SQL
• Data infrastructure and visualization tools
• Data translation for technical and non-technical audiences
• Agronomic concepts, sampling methods, and data quality best practices
• Problem-solving
• Attention to detail and data integrity
• Collaboration, mentoring, or leading analytics projects (added advantage)

• Bachelor’s degree in Data Science, Statistics, Agronomy, or a related field.
• Strong grounding in statistics and machine learning applied to real-world agricultural problems.
• Experience with geospatial analysis, GIS tools, and remote sensing for agricultural insights.
• Proficient in Python/R, SQL, and modern data infrastructure and visualization tools.
• Ability to translate complex data into clear insights for technical and non-technical audiences.
• Demonstrated understanding of agronomic concepts, sampling methods, and data quality best practices.
• Strong problem-solving skills with high attention to detail and data integrity.
• Experience collaborating, mentoring, or leading analytics projects is an added advantage.