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The UN Secretariat in Jakarta, Indonesia seeks a Data Analytics Specialist to support evidence-based decision-making for the UN Sustainable Development Cooperation Framework. You will develop databases, manage data collection, and create dashboards in collaboration with national partners to track SDG progress.
The role emphasizes data quality, MEL outputs, and capacity building across staff and partners, enabling data-driven policy and program decisions within the UNCT framework.
The UN Resident Coordinator Offices (UN RCO) support countries in achieving development priorities and SDGs, operating under the UN Secretariat's Development Operations Coordination Office (DCO). This role, situated within the UN RCO in Jakarta, Indonesia, supports the UN Country Team (UNCT) in advancing evidence-based decision-making for the UN Sustainable Development Cooperation Framework.
This role supports the UN Resident Coordinator (RC) and UN Country Team (UNCT) in Indonesia to enhance evidence-based decision-making for the implementation of the UN Sustainable Development Cooperation Framework (CF). It involves collaborating with government counterparts and spans data management, analytics, strategic partnerships for data and research, monitoring, reporting, and knowledge management. The position aims to accelerate the achievement of Sustainable Development Goals (SDGs) in Indonesia by optimizing statistical efficiency and quality through effective database development, data collection systems, and analytics. The incumbent will interact with internal and external stakeholders to exchange information and best practices, contributing to the UN 2.0 shift anchored in data and digital innovation.
An advanced university degree (Master's or equivalent) in computer science, data science, analytics, statistics, applied mathematics, information management, or a related field is required. A Bachelor's degree with two additional years of qualifying experience may be accepted.
A minimum of two years of progressively responsible experience in data manipulation and analysis, including foundational concepts like data structures and statistical methods, is required. Experience with the data life cycle (collection, wrangling, analysis, visualization, reporting) is desirable. Knowledge of database management, data quality assurance, SQL, and programming languages (Python, R) is also desirable.
Professionalism (strategic and analytical thinking, collaboration, data validation, research, problem-solving), Communication (clear speaking and writing, active listening, effective tailoring of messages), Technological Awareness (understanding and applying technology, willingness to learn new technologies).
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