Associate Data Specialist

United Nations

Location:
Antananarivo, Madagascar
Grade:
NO-B
Category:
Professional Staff
Posted Sep 30, 2026Apply by Oct 14, 2026 (7d left)
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The Associate Data Specialist supports the UN Resident Coordinator Office in Antananarivo by developing and implementing data systems, analytics, and reporting tools to optimize statistical efficiency and quality. The role involves data collection, analysis, visualization, and collaboration with internal and external partners to support evidence-based decision-making and monitoring of sustainable development goals.

Responsibilities

  • Develop and implement databases, data collection systems, data analytics, and other analysis, reporting and quality control capabilities; identifies appropriate data sources for analytics projects; identifies new data analysis process-improvement opportunities and strategies that optimize statistical efficiency and quality.
  • Identify, analyze, and interpret trends or patterns, applying statistical methods to structured and unstructured sources of information and data to surface relevant features and variables.
  • Implement process-improvement mechanisms for data analytics tasks; acquires and cleans data from primary and secondary sources; maintains and quality-assures databases and data systems, including UN INFO and CF results data.
  • Develop reports, dashboards, and other tools to effectively summarize findings and convey information to management across the development, humanitarian and peace nexus, supporting RC/UNCT evidence-based decision-making.
  • Contribute to the development of monitoring, evaluation and learning (MEL) products for UN Sustainable Development Cooperation Frameworks using approved indicators and tools.
  • Draft inputs for a wide range of documents/reports, briefings/debriefings, correspondence, etc.
  • Contribute to the development of processes and tools to monitor and analyze model performance and data accuracy.
  • Design internal process improvements: automating manual processes, optimizing data delivery, re-designing architecture for greater scalability.
  • Implement solutions to data-related technical problems and data infrastructure updates.
  • Contribute to the preparation and organization of datasets to ensure data scientists and analysts have the necessary data for feature extraction. Perform routine data processing and quality checks to maintain data integrity.
  • Collaborate with data engineers and data scientists to improve data flows, data quality, etc.
  • Contribute to the creation of basic data visualization outputs to aid decision-making and communications of analysis outputs.
  • Contribute to project tasks, assist with data collection and initial analysis, and report unresolved issues to senior staff.
  • Contribute to the production of data products like reports or newsletters related to data analysis activities.
  • Conduct data collection, cleaning, and preliminary analysis, contributing to the identification of patterns and trends.
  • Compile and clarify data insights and develop supporting materials in preparation for stakeholder communications.
  • Keep abreast of current and emerging trends in data analytics best practices, technologies, and tools, and proposes their application to strengthen the RCO's analytical function.
  • Build staff and partner capacity on data analytics, including delivering trainings and workshops for UN personnel and national counterparts.
  • Support data preparation and preliminary analysis, verification, and pattern identification; contributes to routine reporting and administrative aspects of the work plan.
  • Contribute to the design and development of data science products, including through advanced analytical methods such as artificial intelligence, machine learning, predictive analytics, data and text mining, natural language processing, statistics, and related algorithms and computational approaches, to generate insights not otherwise detectable through standard analysis.
  • Serve as a resource person and informal mentor on data analytics within the RCO, promoting a data-driven culture and knowledge-sharing across results groups.
  • Contribute to data preparation and preliminary analysis, support team members in data verification and routine reporting tasks, help in administrative aspects of the work plan.
  • Assist with activities for monitoring, evaluation and learning cycle to support the MEL group and national counterparts—so that planning, data collection, synthesis, validation and learning loops reinforce monitoring and support national statistical processes and standards.
  • Performs other duties as assigned

Requirements

  • An advanced university degree (Master's degree or equivalent) in computer science, data science, analytics, statistics, applied mathematics, information management, data management, information systems, information science, economic or social sciences, or a related field.
  • A first-level university degree (Bachelor’s degree or equivalent) in combination with two additional years of qualifying experience may be accepted in lieu of the advanced university degree.
  • A minimum of two (2) years of progressively responsible experience demonstrating ability to translate business requirements into technical solutions is required.
  • Demonstrated ability to perform quality assurance of data analysis outputs is required.
  • Demonstrated ability to assess data accuracy and consistency by performing data validation is desirable.
  • Demonstrated skills in data storytelling and data visualization tools such as Tableau, Power BI, Qlik, and R is desirable.
  • Demonstrated skills to communicate complex and technical matters to diverse audiences is desirable.
  • Demonstrated knowledge of data life cycle including data collection, data wrangling, analysis, visualization, deployment, monitoring, and reporting is desirable.

Skills

  • Data Analysis
  • Data Validation
  • Quality Assurance
  • Data Visualization
  • Tableau
  • Power BI
  • Qlik
  • Data Storytelling
  • Data Management
  • Data Collection
  • Data Wrangling
  • Statistical Analysis
  • Technical Solutions Design
  • Reporting Tools
  • Data Lifecycle Management

Languages

English, French