Information Systems Assistant (Data analyst)

MONUSCO/MONUC was established in 1999 under the auspices of the UN Department of Peacekeeping Operations (DPKO).

Within the delegated authority and under the direct supervision of the Chief I&T or designated authority, the UN Volunteer will undertake the following duties:

Business analysis and stakeholder engagement
• Engage mission sections, pillars and other stakeholders to identify operational problems, decision-support needs and opportunities for data-driven improvement.
• Lead or support requirements-gathering activities, including process mapping, data discovery, gap analysis, feasibility assessment and definition of measurable success criteria.
• Translate business requirements into solution designs, prototypes, implementation plans and realistic estimates of resources, dependencies, risks and delivery timelines.
• Advise stakeholders on suitable analytical methods, visualizations and data-storytelling approaches, while constructively challenging requests that do not address the underlying decision need.

Data engineering and analytics infrastructure
• Design, build, test and maintain reliable data extraction, ingestion, transformation and loading pipelines for structured and semi-structured data from databases, spreadsheets, flat files, APIs and other approved sources.
• Develop scalable data models, curated datasets and data-store structures that support consistent reporting, reuse and future advanced analytics.
• Integrate data from multiple operational systems, implement incremental and scheduled processing where appropriate, and reduce unnecessary manual handling.
• Apply sound software and data engineering practices, including modular development, source control, testing, error handling, logging, documentation, deployment and maintainability.
• Assess existing analytics infrastructure and recommend practical improvements to architecture, performance, resilience and cost-effectiveness within the available UN technology environment.

Business intelligence and advanced analytics
• Design and develop basic to complex reports, dashboards, semantic models and analytical applications using Power BI and other approved tools.
• Conduct exploratory, diagnostic and statistical analysis of large and complex datasets to identify patterns, anomalies, trends, risks and operational improvement opportunities.
• Develop meaningful indicators and analytical frameworks in collaboration with business owners, ensuring that definitions, calculations and limitations are transparent.
• Optimize data models, queries and reports for performance, usability, accessibility and reliable refresh.
• Present findings through concise narratives, visualizations and recommendations tailored to technical, operational and senior leadership audiences.

Data governance, quality and protection
• Establish and apply data-quality controls, validation rules, reconciliation processes and issue-resolution procedures across analytics products.
• Contribute to data dictionaries, metadata, lineage documentation, ownership arrangements, access controls, retention practices and common standards.
• Ensure that solutions are developed in accordance with applicable UN information security, privacy, confidentiality and record-management requirements.
• Promote responsible access to data and design solutions that appropriately separate sensitive information according to user roles and operational need.

Project delivery, adoption and knowledge transfer
• Plan and coordinate assigned analytics initiatives, maintaining clear scope, milestones, risks, dependencies, stakeholder communications and delivery documentation.
• Develop prototypes and minimum viable solutions, coordinate testing and user acceptance, incorporate feedback and support a controlled transition into operational use.
• Monitor adoption and effectiveness after deployment and recommend improvements based on user feedback, usage evidence and changing operational needs.
• Provide technical guidance, peer review, reusable standards, documentation, demonstrations and hands-on knowledge transfer to colleagues and business users.
• Collaborate with technical specialists within MONUSCO, RSCE, other UN entities and external partners to adopt relevant standards and good practices.

Innovation and responsible use of AI
• Monitor relevant developments in artificial intelligence, automation and advanced analytics and identify practical use cases that could add measurable operational value.
• Assess the data readiness, governance, security, ethical considerations, human oversight and stakeholder adoption requirements of proposed AI-enabled solutions.
• Support carefully scoped proofs of concept using approved tools and methods, documenting benefits, limitations, risks and prerequisites before recommending broader implementation.
• Demonstrate continuous learning and the ability to investigate unfamiliar technical challenges, test options systematically and develop practical solutions.
• room technologies.

Expected Results
• Reliable, documented and maintainable data pipelines and integrated datasets established for priority analytical use cases.
• Delivery lead times and engineering bottlenecks are reduced, allowing multiple priority analytics initiatives to progress concurrently.
• Reusable data models, standards and governance controls improve consistency, traceability and trust in mission reporting.
• Analytical products address clearly defined decision needs, perform reliably and are adopted by intended users.
• Manual effort and avoidable data-processing delays are reduced through appropriate automation and streamlined workflows.
• Technical documentation, knowledge transfer and peer review strengthen the sustainability of the Data Analytics function.
• A practical roadmap identifying when and how advanced analytics or AI can be introduced responsibly, based on data readiness and operational value.