Description du poste
Position: Agricultural Data Scientist Company: Heifer International Rwanda Location: Huye, Rwanda Experience: 3-5 years of relevant experience Education: Bachelor’s degree in Data Science, Statistics, Agriculture, or related field Employment Type: Full-time Industry: Agriculture & Agribusiness Department: Research & Development Salary: SSP 1,200,000 – 1,800,000 per month Vacancies: 1 Company Overview Heifer International Rwanda is a leading non‑profit organization dedicated to ending hunger and poverty through sustainable agricultural development. Operating across Rwanda, Heifer partners with smallholder farmers, cooperatives, and local governments to provide training, livestock, and innovative technologies that boost productivity and improve livelihoods. As part of a global network, Heifer International Rwanda brings international best practices to the Rwandan context, fostering resilient farming systems and creating long‑term economic growth. The organization’s commitment to community empowerment makes it a premier employer for professionals seeking to make a tangible impact on Rwanda Jobs and the broader development sector. Job Overview The Agricultural Data Scientist will lead the collection, analysis, and interpretation of agricultural data to support evidence‑based decision making across Heifer’s programs in Rwanda. This role involves designing data pipelines, building predictive models, and translating complex datasets into actionable insights that enhance crop yields, livestock health, and market access for farmers. Working closely with agronomists, field officers, and technology partners, the specialist will drive innovation in data‑driven agriculture, contributing directly to the organization’s mission and to Career Opportunities in Rwanda. For more information, visit our website Heifer International . Key Responsibilities Develop and maintain robust data collection frameworks for field surveys, remote sensing, and IoT devices. Analyze large datasets using statistical methods and machine learning to identify trends and predict outcomes. Collaborate with agronomy teams to integrate data insights into program design and farmer training. Create interactive dashboards and visualizations for stakeholders to monitor project performance. Ensure data quality, integrity, and compliance with privacy standards. Publish research findings and contribute to know...