Data Analysis and Validation Officer

Role summary Background and Objective of the assignment The Relief, Employment and Vital Infrastructure for the Vulnerable in Emergencies (REVIVE) Project, funded by the Government of the Republic of Korea (ROK) and implemented by UNDP, seeks to support vulnerable populations through employment generation, livelihood recovery, rehabilitation of community infrastructure, and resilience-building initiatives. The project contributes to improving socio-economic conditions, strengthening community resilience, and increasing access to sustainable livelihood opportunities, particularly for women, youth, and vulnerable households. To support effective Programme implementation, monitoring, and accountability, UNDP seeks to engage a Data Analysis and Validation Officer responsible for ensuring the quality, accuracy, consistency, and reliability of project data. The incumbent will support data validation, quality assurance, database management, monitoring, reporting, and analytical activities to facilitate evidence-based decision-making and effective Programme management. The position will play a critical role in strengthening data management systems, tracking project achievements, validating beneficiary information, measuring performance indicators, and producing analytical reports in line with UNDP standards and donor requirements. Scope of work The Data Analysis and Validation Officer will support programme implementation through systematic data collection, verification, validation, quality assurance, analysis, reporting, and database management. The incumbent will ensure the accuracy and reliability of programme information, support monitoring and evaluation activities, and contribute to evidence-based planning and decision-making. The position requires close coordination with programme teams, field staff, implementing partners, and beneficiaries to ensure data integrity and compliance with UNDP reporting and accountability requirements. Duties and responsibilities Task Description 1. Technical support and system maintenance Provide technical assistance to PMU team, maintain and update AIMS systems, and support the use of digital platforms like SharePoint. 2. Data Validation and Quality Assurance · Verify and validate beneficiary and project data received from field teams and implementing partners. · Conduct routine data quality assessments to identify inconsistencies, duplicates, missing information, and reporting errors. · Ensure the accuracy, completeness, and reliability of programme datasets. · Support beneficiary verification and field validation exercises. · Develop and maintain data quality control procedures and validation protocols. · Document validation findings and provide recommendations for corrective actions. 2. Data Management · Maintain, update, and manage project databases and beneficiary records. · Clean, organize, and consolidate data collected from multiple sources. · Ensure secure storage, confidentiality, and accessibility of project data. · Develop and maintain data tracking systems and reporting templates. · Support the establishment of standardized data management procedures. 3. Data Analysis and Reporting · Analyze quantitative and qualitative data to support programme planning and decision-making. · Produce statistical summaries, trend analyses, beneficiary profiles, and key performance indicators. · Generate monthly, quarterly, and ad hoc analytical reports. · Prepare dashboards, presentations, tables, and visual summaries of programme results. · Provide evidence-based recommendations to support management decisions and programme improvements. 4. Monitoring and Evaluation Support · Support monitoring and evaluation activities through data validation, analysis, and reporting. · Track project progress against targets, indicators, and planned results. · Support baseline assessments, beneficiary surveys, end-line assessments, and other data collection exercises. · Participate in field monitoring missions and beneficiary verification visits. · Identify programme trends, implementation gaps, challenges, and lessons learned through data analysis. 5. Coordination and Programme Support · Coordinate with programme teams, M&E personnel, and implementing partners to improve data quality and reporting processes. · Support data review meetings and follow up on corrective actions related to data quality issues. · Assist in preparing programme reports, presentations, and donor reporting materials. · Participate in meetings with beneficiaries, implementing partners, and UNDP programme teams. 6. Other Duties · Perform any other duties assigned by the supervisor related to data management, validation, monitoring, analysis, reporting, and programme support. Institutional arrangement The Data Analysis and Validation Officer will work under the guidance of the REVIVE Program Manager and report directly to the Technical Specialist - Livelihood. Technical guidance and support will also be provided by the AMIS team. Job requirements Education A high school education is often the minimum, with a university degree in a related field like IT, Marketing, and Business preferred. Experience and Skills · Minimum 3/7 years of relevant experience with a Bachelor's degree or 1 year of experience with a Master's degree. · Demonstrated experience in data analysis, data validation, monitoring and evaluation, and reporting. · Experience supporting livelihoods, resilience, recovery, development, or humanitarian programmes. · Previous experience working with community-based organizations, NGOs, UN agencies, or donor-funded projects is desirable. · Experience managing large datasets, beneficiary databases, and programme information systems. Technical aptitude · Advanced proficiency in Microsoft Excel and Microsoft Office applications. · Strong knowledge of data cleaning, validation, quality assurance, and statistical analysis. · Experience using data collection and management platforms such as Kobo Toolbox, ODK, Comcare, or similar tools. · Familiarity with Power BI or other data visualization platforms is desirable. · Understanding of monitoring and evaluation frameworks, indicators, and reporting systems Competencies · Strong analytical and problem-solving skills. · Excellent attention to detail and commitment to data accuracy. · Ability to collect, clean, validate, analyze, and interpret complex datasets. · Strong report writing and presentation skills. · Ability to identify patterns, trends, and inconsistencies within data. · Effective communication and interpersonal skills. · Strong organizational and time-management skills. · Ability to work independently and collaboratively in a multicultural environment. · Commitment to confidentiality and responsible data management practices. Language Requirements Proficiency in written and spoken English and fluency in local languages, Pashto and Dari is required.