Director, Monitoring, Learning, and Evaluation – AI Access Initiative

🔥 7 minutes ago

🌐 United States, Canada, +2 more countries – Remote

🇺🇸 United States – Remote 🇨🇦 Canada – Remote 🇰🇪 Kenya – Remote 🇮🇳 India – Remote

💵 $142k - $162k / year

⏰ Full Time

🔴 Lead

🤖 Artificial Intelligence

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Evidence Action

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2013

🏥 Healthcare

💼 Consulting

🍽️ Food & Beverage

💰 $120k Seed Round on 2017-03

Healthcare • Consulting • Food & Beverage

Evidence Action is a non-profit organization that scales low-cost health interventions to improve the well-being of millions of people, primarily in Africa and Asia. Their work focuses on child and adolescent health, clean water, maternal and newborn health, neglected tropical diseases, nutrition, and programs to empower women and girls. Evidence Action's data-driven, evidence-based solutions target urgent health needs and provide transformative impact on global poverty. They implement proven interventions such as deworming, vitamin access, safe water initiatives, and syphilis screenings. Evidence Action is recognized for its transparency and high-impact charitable activities.

📋 Description

• Define 2AI's approach to measurement and evaluation across Agriculture, Health, and the Incubator • Set and maintain rigorous MLE standards from design through dissemination • Establish standards for acting on weak or emerging evidence, uncertainty, and key assumptions • Test and create industry best practices for AI-enabled MLE approaches • Explore frontier AI tools and techniques, including LLM-assisted evidence synthesis and agentic analysis pipelines • Design the MLE team structure, recruit first hires, and develop a high-performing team • Set performance standards and build a culture of active feedback • Provide technical supervision and mentorship on complex problems • Advise the Incubator on program assessment and pilot design • Review existing evidence and stress-test hypotheses • Identify evidence gaps and develop stage-appropriate learning plans • Pressure-test outcome and cost-effectiveness models and key assumptions • Design measurement systems, protocols, and data collection processes for live Agriculture and Health programs • Build rapid experimentation, including A/B testing of AI tool features and delivery approaches • Identify high-value portfolio questions and ensure findings reach program and country teams • Own the MLE budget and resourcing plan • Secure buy-in and funding for the MLE function • Communicate methods, findings, and learning to funders and partners • Publish MLE work as public goods

🎯 Requirements

• 10+ years of progressive experience in monitoring, learning, and evaluation, including hands-on leadership of a rigorous quantitative function enabling data-driven decisions in global health or development • An advanced degree in economics, statistics, public health, or another quantitative field, or a comparable mix of advanced training and technical experience; a PhD is optional • Expertise in evaluation design and analysis, including statistically rigorous impact evaluations, process evaluations, and mixed-methods approaches • Experience managing large-scale quantitative evaluations from design through dissemination • Fluency in interpreting existing evidence and translating it into informed program decisions • Track record of building teams and developing senior technical talent, including setting performance standards and giving clear, frequent feedback • Clear understanding of and experience in using AI in the MLE process • Quantitative modeling under uncertainty, including outcome and cost-effectiveness estimates for early-stage programs • Comfort with ambiguity and experience setting up new systems, structures, and standards where none exist • Ability to make tough choices among imperfect options and communicate tradeoffs • Technical communication skills for MLE specialists, funders, government counterparts, and non-technical audiences • Relationship-building with program teams, partners, and peer organizations, with external presence through publications, conference talks, or similar platforms • Applicants must be legally authorized to work in the country where they are based • Evidence Action cannot sponsor or take over sponsorship of an employment visa • Experience with R, Python, Stata, or similar tools is a plus • In-the-field experience in low- and middle-income countries is nice to have • Experience supporting government partners with data-led decisions on program implementation is nice to have

🏖️ Benefits

• Comprehensive benefits package • Health insurance • Vision insurance • Dental insurance • Retirement plans • Generous and flexible leave options • Other employee perks • International travel (~15-20%)

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