Overview
The Data Specialist will develop and implement databases, data collection systems, and data analytics to optimize statistical efficiency and quality. The role supports the development of monitoring and evaluation products and capacity building for data analytics.
Tasks Summary
- Develop and implement databases, data collection systems, data analytics and other strategies that optimize statistical efficiency and quality.
- Identify, analyse, and interpret trends or patterns, using statistical methods to identify relevant features and variables in structured and unstructured sources of information and data.
- Develop and implement various analysis, reporting and quality control capabilities; identify appropriate data sources for analytics projects; locate and define new data analysis process improvement opportunities.
- Support the development of monitoring, evaluation and learning (MEL) products for UN Sustainable Development Cooperation Frameworks, leveraging UN organizations’ systems, UN approved indicators, Power BI and other approved tools.
- Keep abreast of UN efforts in co-design (with the national statistical partners) digital tools and dashboards that track progress against the national SDG indicator framework, ensuring interoperability between the national gateway, and other official platforms (using SDMX standard where appropriate).
- Develop reports, dashboards or other tools to effectively summarize findings and convey information to management.
- Create interactive and static data visualizations and employ advanced features of data visualization tools to aid decision-making and communications of analysis outputs.
- Drafts inputs for a wide range of documents/reports, briefings/debriefings, correspondence, etc.
- Establish communication and cooperation with other parts of the organization to request data and express data needs.
- Provide support to integrate monitoring milestones, indicators and evidence streams into common data pipelines, ensuring alignment with the Cooperation Framework and Funding Compact.
- Support UNCT statistical capacity-building by mapping and sequencing agency‐specific technical assistance in line with Cooperation Framework, broker pooled funding opportunities for National Statistical System (NSS) priorities, and support convenings of data-partners between government, donors and civil society.
- Keep abreast of the current and emerging trends and developments in data analytics best practices, technologies and tools, and update management with findings and suggestions.
- Support the assessment of model evaluation using appropriate validation metrics to ensure the model is comprehensive and supports the organizational objectives.
- Conduct activities aimed at building capacity of staff on data analytics, including trainings for staff members and other personnel.
- Deliver training on results-based management, evaluation techniques and use of monitoring, evaluation and learning for staff members and government partners.
- Collaborate on the end-to-end monitoring, evaluation and learning cycle by working with 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.
- Support the development of materials for external and internal audits through data preparation, compliance tracking, and report generation.
Experience Requirements
- A minimum of five (5) years of progressively responsible experience demonstrating the knowledge of foundational concepts in data manipulation and data analysis such as data structures, statistical methods is required.
- Demonstrated knowledge of data life cycle including data collection, data wrangling, analysis, visualization, deployment, monitoring, and reporting is required.
- Demonstrated skills in data storytelling and data visualization tools such as Tableau, Power BI, Qlik, and R is required.
- Demonstrated programme/Project management skills is desirable.
- Demonstrated skills in developing and executing training programs and curricula across different levels and target audience using various methods is desirable.
- Demonstrated skills in strategic thinking, analytical thinking and coordination is desirable.
Qualification 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 or economic or social sciences, or a related field is required.
- A first-level university degree (Bachelor's degree or equivalent) in combination with two (2) additional years of qualifying experience may be accepted in lieu of the advanced university degree.
- Successful completion of both degree and non-degree programs in data analytics, business analytics or data science programs is an advantage.
