Data Management Specialist

About the role

The Data Management Specialist will lead the collection, analysis, interpretation and presentation of school performance and student outcome data. Working closely with schools, educational leaders and improvement partners, the role develops analytical tools and generates insights that drive system-wide improvement.

Key responsibilities

• Design and manage data collection systems, evaluation instruments, sampling frameworks and analytical tools.
• Analyse complex educational datasets and translate findings into clear, actionable recommendations.
• Produce high-quality reports, dashboards, visualisations and performance summaries for internal and external stakeholders.
• Develop and maintain performance databases, benchmarks and data repositories.
• Lead advanced statistical analyses such as factor analysis, structural equation modelling, predictive analytics, forecasting and attribution modelling.
• Support schools and stakeholders in strengthening their data collection, management and evaluation capabilities.
• Identify trends and patterns through proactive data mining to inform strategic decision-making.

Required profile

• Bachelor’s degree in Data Science, Statistics, Management Information Systems, Psychometrics, Educational Measurement, Research Methods or a related field (post‑graduate qualification desirable).
• Professional experience in data management, analytics, psychometrics, performance measurement, educational research or monitoring and evaluation.
• Proven ability to work with large, complex datasets and apply advanced statistical techniques.
• Strong expertise in data capture, cleaning, quality assurance and reporting.
• Excellent analytical, problem‑solving and communication skills, with the ability to convey complex findings to technical and non‑technical audiences.

Required skills

• SPSS or comparable statistical analysis software.
• Power BI or equivalent business intelligence and dashboard platform.
• Advanced data visualisation and dashboard development.
• Microsoft Excel and Access.
• Item Response Theory (IRT) and psychometric analysis.
• Exploratory and Confirmatory Factor Analysis.
• Structural Equation Modelling (SEM) – knowledge of AMOS or similar.
• Predictive modelling, forecasting and advanced quantitative analysis.