ASSOCIATE DATA SPECIALIST, NOB
Overview
The Associate Data Specialist will implement databases, data collection systems, and data analytics to optimize statistical efficiency and quality. The role involves contributing to the identification, analysis, and interpretation of trends and patterns in data.
Key Responsibilities
- Implement databases, data collection systems, data analytics and other strategies that optimize statistical efficiency and quality.
- Contribute to the identification, analysis and interpretation of trends or patterns, using statistical methods to identify relevant features and variables in structured sources of information and data.
- Implement process improvement mechanisms for data analytics tasks; acquire and clean data from primary or secondary sources and maintain databases/data systems.
- Contribute to 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.
- Contribute to 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.
- Contribute to the activities for integrating monitoring milestones, indicators and evidence streams into common data pipelines based on the Cooperation Framework and Funding Compact.
- Assist in UNCT statistical capacity-building by contributing to the mapping and sequencing agency‐specific technical assistance in line with Cooperation Framework.
- 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., and assist with identifying findings and suggestions.
- Assist in conducting outcome-level analysis and contribution/attribution studies using mixed-methods to inform UN reporting and UN-commissioned evaluations.
- 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 collection and preliminary analysis to support the preparation and verification of data used in model assessments.
- 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.
- Assist in delivery of 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.
- 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.
- 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.
- Performs other duties as required.
Required Experience
A minimum of two (2) years of progressively responsible experience in data life cycle including data collection, data wrangling, analysis, visualization, deployment, monitoring, and reporting is required. Demonstrated knowledge of foundational concepts in data manipulation and data analysis such as data structures, statistical methods is required. Demonstrated skills in relational databases (SQL) and programming languages (Python, R) is required.
Qualifications
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 additional years of qualifying experience may be accepted in lieu of the advanced university degree.