Key Purpose Statement
To collect, organize, process and analyse data for a variety of academic concerns ranging from improving cohort throughput to identifying gaps in student achievement – anything requiring data to make better academic decisions. An element of training is also required.
Key Responsibilities:
Collection, organisation, processing and analysis of learning and teaching data to drive the implementation of the Brand academic strategy and delivery to the Brand academic standards
- Stewardship of brand-related academic data to ensure integrity.
- Develop standard dashboards to track the main Academic KPIs per campus, phase, subject and grade.
- Develop Brand Academic delivery standards for each phase, grade and subject.
- Based on the analysis of teaching and learning data from all Brand academic platforms (AdvLearn, LMS, Academic apps,…), identify continuously areas for improvement. Formulate action plans and roadmaps for the Brand and campuses to implement the Brand academic strategy and deliver to the Brand academic standards, consistently across the phases.
- Monitor implementation of action plans and effectiveness. Formulate action plan amendments when necessary.
Research to support the development of the Brand Mid-term academic plan with the required innovation milestones.
- Support research output by offering data analysis support for various campus research initiative.
- Research information relevant to the improvement of Teaching and Learning.
Procedure development and maintenance.
Training of Academic staff in academic systems and procedures
- Develop user how-to-guide and/or procedures to facilitate the implementation of the Academic learning and teaching platforms.
- Training of stakeholders in related systems and procedures.
- Monitor usage rate of the Brand academic platforms and assess if the usage is aligned with the intended purpose. Identify training requirements and develop training material.
Competencies
Skills Requirements
- Strategic insights
- Critical Thinking
- Self-Management
- Data tools (SQL, Excel, R/ Python, PowerBI)
- Data mining/ machine learning
- Data visualisation and presentation
- Data Modelling
- Training
Behavioural Attributes
- Interpersonal skills/ teamwork
- Persistence/ patience
- Curiosity
- Independence
- Logical thinking
- Agility
Qualifications
- Bachelor's degree in Mathematics, Statistics, Computer Science, or a related field.
- Honours degree in the above-mentioned disciplines would be an advantage.
- Power BI experience is a must.
- 3-5 years Data Analyst experience / 3-5 years Data Engineer experience.
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Drivers required.
