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Manager, MLE, KMC Consultant

Evidence Action
CompanyEvidence Action
CategoryUncategorised
LocationMonrovia
RemoteOn-site (inferred)
EmploymentNot stated
LevelNot stated
SalaryNot stated by the employer
Posted28 Jul 2026
Last verified9 Aug 2026
SourceEmployer ATS (workable)
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Description
About Evidence Action Evidence Action is a global nonprofit organization with an approach distinctive in international development—we exclusively scale interventions that are backed by strong evidence and can be delivered with exceptional cost-effectiveness. Since our founding in 2013, we have reached over 515 million people globally with our interventions. We deliver high impact for every dollar spent, as recognized by GiveWell , The Life You Can Save , and Charity Navigator . We do development differently. We take a data-driven approach to identifying, scaling, and continuously improving programs that deliver immense impact, ensuring these solutions measurably improve the lives of millions. Our Deworm the World Program has helped governments in Africa and Asia deliver over 1.8 billion childhood deworming treatments, improving health, education, and incomes. Safe Water Now provides sustained safe water access to over 10 million people in Africa, preventing childhood illness and deaths.  We drive innovation: Our Accelerator builds the next generation of exceptional programs, taking an approach most similar to a venture capital model. We are ruthless in exiting programs that do not meet our criteria; those that advance deliver outsized impact for millions of people.  We are global. Across nine countries in Africa and Asia, our 700+ people are united by a tremendous passion for our mission and impact. We are strong because of our diversity of experience, geography, and background—with over 90% of our people in the countries where our impact is focused.  We have big ambitions. Over the next decade, we’re setting our sights higher: We aim to reach over 600 million people globally to fulfill our vision of a world where hundreds of millions of people in the poorest places have better opportunities and their lives are measurably improved. We believe in bold and urgent action—because poverty doesn’t wait, and neither should we.  We need great people. Our success to date is due to the collective work of our amazing staff. To achieve our ambitious goals, we are looking for people who share our passion for evidence, cost-effectiveness, and scale. We seek individuals who take an entrepreneurial approach, enjoy tackling hard problems, and have a bias to action and results. If our vision and approach excite you as much as they do us, we invite you to join us. Job Purpose Kangaroo Mother Care is a WHO-recommended intervention for preterm and low birth weight newborns shown to reduce neonatal mortality by up to 32% compared to conventional care. Despite strong evidence and national policy inclusion, KMC implementation in Liberia remains concentrated in a small number of major hospitals, leaving most facilities without the protocols, training, or quality systems needed to deliver KMC reliably.  Evidence Action is launching a KMC technical assistance pilot working through MoH structures to build government capacity to support, monitor, and sustain high-quality KMC practice across pilot facilities. The pilot will span 12 months and focus on providing technical assistance to increase KMC coverage, improve KMC initiation timing, and minimize mother-infant separation during hospitalization. Duties and Responsibilities Formative research qualitative data collection and analysis •     Lead focus group discussions and key informant interviews at pilot facilities and in surrounding communities  •     Contribute to Focus Group Discussion (FGD) and Key Informant Interview (KII) guide design •     Take primary responsibility for the quality of qualitative data collected, including probe depth, note completeness, and recording quality •     Lead transcription review and initial thematic organization of qualitative data •     Identify emerging themes, contradictions, and gaps in the qualitative data Data c