Data Specialist, NOC

The Data Specialist supports the UN Resident Coordinator Office in Georgetown by developing and implementing databases, data collection systems, and data analytics to optimize statistical efficiency and quality. The role involves data analysis, reporting, capacity building, and collaboration with UN agencies and national partners to support the achievement of the Sustainable Development Goals.

Responsibilities

• 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.
• Document requirements, background information and methodology and establish documentation practices and standards for other staff to follow.
• Create interactive and static data visualizations and employ advanced features of data visualization tools to aid decision-making and communications of analysis outputs.
• Lead production of data products such as reports or newsletters related to data analysis activities.
• Draft 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.
• Collaborate with data engineers and data scientists to improve data flows, data quality, etc.
• 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.
• Conduct outcome-level analysis and contribution/attribution studies using mixed-methods to inform UN reporting and UN-commissioned evaluations.
• Identify gaps in the NSS using relevant statistical capacity monitoring tools and recommend coordinated UN responses, highlighting opportunities to leverage big-data pilots, citizen-generated data, or geospatial solutions.
• 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.
• Contribute to the provision of ‘data clinics’ on relevant topics, including gender-responsive statistics, new census methodologies, drawing on UN expertise and global curricula from the statistical community.
• Deliver trainings and workshops on data analytics tailored to different audiences as appropriate.
• Support projects execution by conducting robust data analysis and collaborate with other team members to ensure that projects adhere to work plan objectives.
• Supervise and guide other colleagues in the data-centric roles.
• Execute and oversee specific projects and activities, ensuring effective use of resources and alignment with planned objectives.
• 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.
• Utilize acquired resources to build analysis, reporting and quality control.
• Support the development of materials for external and internal audits through data preparation, compliance tracking, and report generation.
• 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, economics 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.
• An active certificate in relevant areas such as data engineering, data management, or cloud platforms (e.g., AWS, Azure) is desirable.
• A minimum of five (5) years of progressively responsible experience demonstrating the knowledge, skills and ability to translate business requirements into technical solutions is required.
• Demonstrated skills in data storytelling and data visualization tools such as Tableau, Power BI, Qlik, and R 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.
• Experience in providing strategic support to research and data analysis, knowledge management or project/programme management in the context of development cooperation or related area is desirable.
• Demonstrated skills in developing and executing training programs and curricula across different levels and target audience using various methods is desirable.
• Knowledge of data life cycle including data collection, data wrangling, analysis, visualization, deployment, monitoring, and reporting is required.
• Fluency in English at UN Level II for reading, writing, listening and speaking is required.

Skills

• Data Engineering
• Data Management
• Cloud Platforms
• AWS
• Azure
• Data Storytelling
• Data Visualization
• Tableau
• Power BI
• Qlik
• Quality Assurance
• Data Validation
• Data Analysis
• Training Program Development
• Data Life Cycle
• Data Collection
• Data Wrangling
• Data Reporting

Languages

English