The World Agroforestry Centre-Research Associate – Socioeconomics Nairobi

CIMMYT is seeking an experienced professional to support Agricultural Economy and Value chain on all data analysis for ongoing projects with both qualitative and quantitate data.

1.      Overseeing Field Surveys. Conduct regular field visits to supervise data collection and follow-up with partners. Data entry, cleaning, and management of survey data. Implement farm household, market and consumer surveys. Collect and manage secondary data. 2.      Data Management. Locate, assemble, and analyze secondary data relevant for socioeconomics and policy research in maize and wheat systems. Assist in managing and updating existing socioeconomic databases on stakeholder contacts, changing livelihood strategies, poverty and markets. 3.      Data Analysis and Reporting Conduct econometric analysis of survey and other data using STATA or other standard statistical software. Conduct literature reviews and assist in preparing strategy documents, research reports and policy briefs to strengthen research and publication efforts. Participate in the development of communication materials to enhance the impact of strategic socioeconomics and policy research in different regions. 4.      Other duties. Develop work-plans and budgets for subcontractors and collaborators. Maize and wheat productivity in different regions. Handle logistics arrangement related to field planning, data collection and stakeholder meetings/workshops. Perform other duties and miscellaneous tasks as required and as assigned by the supervisor. Requirements Master’s/ bachelor’s degree in Agricultural Economics from a reputable university. At least 3 years’ experience in Research activities. General experience in data collection and analysis, planning and implementing mixed methods in data collection. Excellent written and oral communication skills in English.

Master’s/ bachelor’s degree in Agricultural Economics from a reputable university. At least 3 years’ experience in Research activities. General experience in data collection and analysis, planning and implementing mixed methods in data collection. Excellent written and oral communication skills in English.