Associate Data Specialist

The Associate Data Specialist supports the UN Resident Coordinator Office in Gaborone by managing data collection systems, performing data analytics, and contributing to monitoring, evaluation and learning (MEL) products under the UN Sustainable Development Cooperation Framework. The role involves coordinating data initiatives, developing analytical products, and strengthening data-driven planning and reporting to support SDG monitoring and Cooperation Framework implementation.

Responsibilities

• Manage the implementation of data collection systems, data analytics and other strategies that optimize statistical efficiency and quality.
• Lead identification, analysis and interpretation of trends or patterns, using statistical methods to identify relevant features and variables in structured sources of information and data.
• Coordinate process improvement mechanisms for data analytics tasks; acquire and clean data from primary or secondary sources and maintain databases/data systems.
• Lead the development of reports, dashboards or other tools to effectively summarize findings and convey information to management.
• Track and report on progress regarding department specific data initiatives.
• 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.
• Contribute to data collection and gathering business requirements across departments to identify pain points and support data-driven analysis.
• Compile and clarify data insights and develop supporting materials in preparation for stakeholder communications.
• Keep abreast of the current and emerging trends and developments in data analytics best practices, technologies, tools, etc.
• Contribute to data collection and preliminary analysis to support the preparation and verification of data used in model assessments.
• Contribute to the design and development of data science products to reveal insights and to provide an understanding or knowledge of the data that would otherwise not be detected without the application of advanced analytical methods such as artificial intelligence, machine learning, predictive analytics, data and text mining, natural language processing, statistics, and use of relevant algorithms and computational approaches.
• Contribute to the development of processes and tools to monitor and analyze model performance and data accuracy.
• Contribute to activities aimed at building capacity of staff on data analytics, including trainings for staff members and other personnel.
• Contribute to the trainings and workshops on data analytics.
• Contribute to the identification of gaps in the NSS using relevant statistical capacity monitoring tools and assist with the identification of solutions.
• 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.
• Lead the development of monitoring, evaluation and learning (MEL) products for UN Sustainable Development Cooperation Frameworks using approved indicators and 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 for interoperability between the national gateway and other official platforms.
• Assist in UNCT statistical capacity-building by contributing to the mapping and sequencing agency‐specific technical assistance in line with Cooperation Framework.
• 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.
• Perform other related tasks 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, 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.
• A minimum of two (2) years of progressively responsible experience demonstrating the knowledge, skills and ability to translate business requirements into technical solutions, is required.
• Knowledge of foundational concepts in data manipulation and data analysis such as data structures and statistical methods is required.
• Knowledge of the data lifecycle including data collection, data wrangling, analysis, visualization, deployment, monitoring, and reporting, especially in the context of monitoring and evaluation of UNSDCF, is required.
• Knowledge in database management to extract, transform, and load data from various sources is required.
• Demonstrated skills in data storytelling and data visualization tools such as Tableau, Power BI, Qlik, and R is required.
• Demonstrated ability to trouble-shoot and solve complex data problems, is required.
• Demonstrated experience and skills to communicate complex and technical matters to diverse audiences is required.
• Experience and knowledge of core data science and analytics concepts, including statistics and predictive modelling is desirable.
• Experience or skills in data integration tools such as Jupyter, Matlab, Knime, SPSS, and SAS is desirable.

Skills

• Data Manipulation
• Data Analysis
• Statistical Methods
• Data Lifecycle Management
• Data Collection
• Data Wrangling
• Data Visualization
• Tableau
• Power BI
• Qlik
• Database Management
• ETL
• Data Storytelling
• Troubleshooting Data
• Technical Communication
• Predictive Modelling
• Data Integration
• Jupyter
• Matlab
• Knime
• SPSS
• SAS

Languages

English