Lecturer (Big Data Analytics) / School of Informatics & IT

[What the role is]

[What you will be working on]

• Conduct full-time and part-time teaching in areas related to Data Analytics, Artificial Intelligence (AI), Machine Learning, Data Engineering, Data Management, and foundational ICT modules.
• Develop and deliver curriculum in emerging AI technologies, including Generative AI, Large Language Models (LLMs), Agentic AI, Retrieval-Augmented Generation (RAG), and Responsible AI.
• Deliver mathematics modules (e.g. calculus, linear algebra, probability, and statistics) contextualised for IT and AI applications.
• Design, develop, review, and maintain curriculum, course materials, and assessments, and recommend enhancements to improve student learning outcomes, performance, and employability.
• Develop students’ capabilities in project-based work, including e-learning and self-directed learning.
• Guide students in AI and analytics projects involving real-world datasets, predictive analytics, machine learning, and AI-powered applications.
• Coach and mentor students to support their academic and professional development.
• Contribute to School initiatives through participation in outreach programmes, committee work, projects, and events.

[What we are looking for]

• Relevant qualification in Mathematics, Statistics, Information Technology, Computer Science, Business Analytics, Data Science, Artificial Intelligence, or a related discipline.
• At least 7 years of relevant industry experience, preferably in areas such as Data Science, Data Engineering, Data Warehousing, Data Management, Data Analytics, Machine Learning, Agentic AI, and/or Text Analytics.
• Familiarity with analytics, AI, and data platforms such as Power BI, Tableau, R, Python, SQL, KNIME, Alteryx, Snowflake, and cloud technologies (e.g. AWS, Azure).
• Experience with machine learning frameworks and AI development tools, including Generative AI (Gen AI) and Agentic AI.
• Demonstrated competence and strong interest in teaching Analytics, AI, Machine Learning, Data Science, and related mathematical subjects.
• Ability to work both independently and collaboratively, with an interest in engaging and supporting teenagers and young adults.
• Strong written and verbal communication skills.
• Willingness to contribute to publicity and outreach initiatives.