Innovations for Poverty Action (IPA) seeks a Research Associate to manage a study that examines how individuals weigh the risks and benefits of migration, and whether exposure to conflict distorts this process.
This will be the first randomized controlled trial to assess effects of providing information on risks and outcomes through door-
to-door campaigns and social media communications on actual migration decisions, and will be implemented in Edo and Delta states.
The Principal Investigators are Alexandra Scacco (WZB Berlin Social Science Center), Bernd Beber (WZB Berlin Social Science Center), Florian Foos (King’s College London), Macartan Humphreys (WZB Berlin Social Science Center and Dept.
of Political Science, Columbia University), and Dean Yang (Department of Economics and Ford School of Public Policy, University of Michigan).
The Research Associate will work closely with the Senior Research Manager, Principal Investigators, and other IPA country office staff to oversee all aspects of the research study.
The Research Associate will initially be based at the IPA country office, but will subsequently be located in Benin City with frequent regional travel.
This position provides an excellent opportunity to gain extensive hands on experience in a field setting and to have significant management responsibility in a vibrant organization undertaking cutting edge development research.
Key areas of involvement will include : designing survey questionnaires, recruiting, training and managing survey teams, designing and supervising logistics for the field activities, cleaning and analyzing survey data, assisting in the writing of project reports and policy memos, and liaising with key government and nongovernmental stakeholders.
The work will develop your analytical and management skills and require your full commitment in a challenging environment.
Throughout the life of the project, the Research Associate will be expected to carry out the following activities :
translation of the survey into applicable local languages.
correct the errors of staff iteratively to ensure the data is of the highest quality.
Additional preferred qualifications :