About Evidence Action
At Evidence Action, we deliver data-driven interventions that transform lives at an unprecedented scale. We identify neglected global health issues and deploy proven solutions, forging healthier futures for generations.
Our model operationalises leading academic research (including from Nobel-winning economists). We measure progress and outcomes at every stage to ensure we’re making a real impact for people living in poverty and suffering from preventable or treatable health issues. Operating across 11 countries, our team of 900+ has reached over 500 million people, working closely with governments to scale these interventions.
Our Deworm the World program has delivered over 2 billion treatments, significantly reducing worm prevalence and generating more than $23 billion in lifetime productivity gains.
Through Safe Water Now, we’ve saved the lives of over 15,000 children.
Our Accelerator explores untapped opportunities in global health, testing low-cost interventions with the greatest potential to save and improve lives.
At Evidence Action, your colleagues are your greatest asset. You'll partner with high-caliber colleagues in an environment blending innovation, autonomy, and teamwork. Our team excels in disruptive thinking and believes in rolling up our sleeves to get things done. If you're looking to work flexibly and with purpose, join a team that delivers measurable change for millions.
Job purpose
The Associate, MLE, South West is a member of the Monitoring Learning and Evaluation Department and is responsible for supporting all Evidence Action’s Monitoring and Evaluation activities under the Small Quantity Lipid-Based Nutrient Supplement (SQLNS) and Multiple Micronutrient Supplementation (MMS) project in FCT, Kaduna and Plateau State, Nigeria.
In line with the 2021 WHO recommendations, FMOH is coordinating implementation research on optimizing the uptake and adherence of MMS as a replacement for IFA supplementation in Nigeria. The results of these studies will be used for decision-making on MMS scale up in-country. Planning to ensure that sufficient volumes of quality UNIMMAP on MMS are manufactured locally. There is a need for integration and strengthening of government-partner coordination for MMS Research and Programming at National and Sub-national levels.
This is an exciting position that involves supporting the state with routine data management, monitoring data collection, training of data collection teams, management of stakeholder relationships and implementing quality assurance and quality control measures during data collection and management.
Duties and responsibilities
Data Collection and Vendor Management
- Support the sourcing for vendors to provide data collection service to Evidence Action in Nigeria in the assigned State/Zone
- Oversee vendor data collection activities and verify deliverables and milestones for all components for payment
- Verifying and validating data collected by data collection vendors and the state through data reviews, checks (e.g., data validation, infield supervision, and back checks), and field visits.
- Oversee vendor recruitment activities in the zone and provide technical support and advice in line with Evidence Action’s requirements.
- Support the review of the Technical and Financial proposal submitted by IM firms during bids Evidence Action is an Equal Opportunity Employer
- Facilitate the onboarding of IM firms after the signing of contracts for SQLNS and MMS activities.
Coordinating between MLE, Program, Government and Partners
- Represent MLE in program meetings with partners and government (in the supported states) where MLE presence is needed.
- Support state program planning with M&E-related tasks and ensure data is correctly captured, collected, and documented and available for planning and implementation.
- Lead and manage communication with MLE-related stakeholders, providing updates and briefs for activities requiring regular updates to program stakeholders.
- Collaborate with the program team to fully understand program needs for data and translate that back to the necessary MLE delivery team/members for necessary action: support MLE component of program-related tasks
- Support the program during extensive travel to selected sites for spot checks
Training and Field Monitoring
- Independently or in collaboration with the IM firm, lead the training of enumerators, data extractors, etc., on data collection protocols before data collection.
- Support training of government officials on key MLE components or data collection tools, and data management during State, LGA, health facility, or community-level trainings
- Support and supervise data collection teams during monitoring data collection and treatment data collection.
- Ensure training materials, surveys, and training slides are up to date and consistent with the object of training.
Data Collection and Reporting (IM data, Treatment data, Supportive Supervision Data)
- Support (Sternly) Baseline data collection efforts (if applicable)
- Setup and lead data review meetings at LGA and Ward levels
- Support quarterly health facility visits and spot checks. Including data audits and desk reviews at selected sites.
- Support in the development and contextualization of the data tools, review of existing tools, and incorporation of best practices into tool development.
- Design and maintain KPI tracking tools to measure program progress and provide updates to the team.
- Support data cleaning processes together with firms/teams prior to analysis.
- Support state data reporting team to submit accurate and timely treatment data to partners and National after each treatment round
- Support the data learning team to draft process monitoring and coverage validation reports after each deworming round
- Support the IM firm to submit timely and accurate reports on field monitoring activities conducted to Evidence Action
- Lead annual coverage surveys in the designated states.
Other
- Accurately and timely raise issues/suggestions/areas of concerns around process monitoring
- Advise the program and MLE team on real-time security situations in the zone.
- Clear with the security department before field trips.
- Perform any other monitoring, evaluation, and learning duties as may be required and assigned, including supporting other team members or projects temporarily.
Requirements
Qualifications
- Mathematics; a postgraduate degree will be an added advantage.
- 4+ years of program M&E experience in Nigeria specifically related to public health programs.
- Strong technical skills and capacity, with at least 2 years of practical experience managing and working directly with large teams for data collection;
- Strong IT skills related to data collection and management using data collection platforms and software such as Spreadsheets Google Sheet, MS Excel, SPSS etc
- Experience programming and using electronic data collection platforms, specifically Open Data Kit (Survey CTO).
- Data management and reporting skills.
- Excellent team management, presentation, communication, and interpersonal skills.
- Willing to travel on short notice, to multitask, to work in ambiguity, and to respond to instructions from multiple sources.
- Naturally inquisitive, detail-oriented, and organized;
- Inspired by Evidence Action’s mission gather evidence needed to bring proven interventions to scale, improving the lives of millions;
- Ability to speak the local language is a stern requirement.
Top Skills
Similar Jobs
What you need to know about the San Francisco Tech Scene
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine


