Location: Guma, Makurdi
The Data Analyst will support the effective implementation of Monitoring, Evaluation, Accountability, and Learning (MEAL) activities of the SIDPIN interventions by ensuring high-quality data collection, analysis, reporting, and utilization. The role is critical in strengthening evidence-based programming, accountability to affected populations (AAP), and adaptive management across interventions, including Cash and Voucher Assistance (CVA/MPCA), protection, and livelihoods.
The position contributes to improving programme quality, transparency, and impact by generating timely and accurate data insights, ensuring compliance with donor requirements, and supporting informed decision-making in humanitarian contexts.
Key Responsibilities:
- Design, deploy, and manage data collection tools using platforms such as Kobo Toolbox, ODK, and Excel in line with MEAL frameworks, ensuring alignment with sector standards (e.g., Protection, Cash & Voucher Assistance).
- Assist in developing reporting templates and support field teams on tool usage and digital platforms to ensure accurate, real-time data capture. Lead data cleaning, validation, and quality assurance processes in accordance with organizational data quality standards.
- Lead the cleaning, validation, and quality assurance of collected data, ensuring compliance with organizational and sector-specific data quality standards.
- Maintain harmonization and consistency of data across sectors, partners, and reporting platforms to support coherent information management.
- Conduct quantitative and qualitative analysis of programme and protection monitoring data, including Multi-Purpose Cash Assistance (MPCA) performance, protection trends, beneficiary satisfaction, and program outcomes.
- Produce analytical outputs such as dashboards, infographics, maps, Situation Reports (SitReps), and donor reports to inform programme design, adaptive management, and evidence-based decision-making.
- Support analysis of feedback and complaints data through Accountability to Affected Populations (AAP) mechanisms to identify systemic issues and recommend improvements.
- Develop clear and accessible data visualizations to communicate findings to programme teams, sector coordination platforms, and external stakeholders.
- Support information management systems for protection monitoring and programme reporting, ensuring actionable insights are disseminated effectively.
- Ensure adherence to data protection principles, including secure storage, controlled access, and confidentiality of personally identifiable information (PII), particularly for vulnerable populations.
- Apply ethical standards in all data processes, including informed consent, confidentiality, and risk mitigation, in alignment with protection, safeguarding, and humanitarian principles.
- Contribute to organizational learning by documenting lessons learned, supporting evaluations, and facilitating reflection processes to improve programme quality and sustainability.
- Provide technical support and guidance to field staff on data collection, analysis, and reporting processes.
Required Qualifications & Experience
- Bachelor’s degree in Statistics, Actuarial Science, Economics, or related field.
- Minimum of 3–5 years of progressive professional experience in data analysis, information management, or MEAL within humanitarian and/or development programmes.
- Demonstrated experience in designing and managing data collection systems and tools (e.g. KoboToolbox, ODK, CommCare, MS Excel)
- Strong analytical skills using Excel, SPSS, STATA, R, or similar tools
- Strong skills in data visualization and communication using tools such as Excel, Power BI, Tableau, or similar platforms
- Strong understanding of core humanitarian principles and experience working in fragile or emergency contexts highly desirable.
Core Competencies
- Analytical thinking and attention to detail
- Ethical data handling and confidentiality
- Problem-solving and critical thinking
- Communication, Strong analytical and visualization skills
- High attention to detail and data accuracy
- Ability to communicate complex data clearly
- Knowledge of data protection and confidentiality principles
- Results-oriented with strong planning and organizational ability
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