Lecturer - Module Coordinator – Data Science

Job description

• Oversee and manage the development or review of study guides (full or wrap-around) 

• Seek feedback from all stakeholders and keep a record of required changes to study guides in anticipation of the review cycle 

• Monitor the appropriateness of the prescribed textbook and editions 

• Ensure continued alignment between study guide and textbook, where applicable 

• Update study guides to cater for new textbook editions 

• Draft all formal assessments for allocated modules 

• Consider internal and external pre-moderation feedback and implement changes as required 

• Conduct internal pre-moderation for modules in field of expertise 

• Conduct annual meetings with all campus lecturers to discuss the assessment strategy 

• Appoint suitably qualified internal and external moderators 

• Brief markers and moderators, and provide content support during the marking process 

• Mark a prescribed minimum number of assessments (+- 3) to fine tune marking guideline/memorandum 

• Consider markers’ reports and decide on appropriate action 

• Consider moderators’ reports and decide on appropriate action, in consultation with campus lecturers, HOS and subject coordinator (if any)
• Conduct post-assessment meetings with all campus lecturers to reflect on success/concerns with assessments 
• Consider and analyse cross-campus success rates 
• Sign off on assessment results 
• Actively participate in the investigation/management of Red/Fire module status 

• Conduct research in the field of expertise and/or learning design in the field of expertise 

• Attend both internal and external training sessions, workshops, and conferences to enhance skills in module design and assessment 

• Stay informed about emerging trends in higher education and instructional methodologies 

• Engage with industry, professional networks and associations to enhance collaboration and knowledge sharing
• Actively collaborate with campus lecturers to continuously enhance the learning journey

• Design and draft materials needed for the course environment (announcements, etc.) 

• Populate and maintain the Canvas Blueprint course environment for modules owned

• Develop and deliver at least two lectures per module per semester for CL students, online live 

• Record at least two online lectures for DL students per semester per module 

• Deliver guest lectures in the field of expertise on STADIO modules as appropriate 

• Conduct research in the field of expertise and/or learning design in the field of expertise 

• Attend both internal and external training sessions, workshops, and conferences to enhance skills in module design and assessment 

• Stay informed about emerging trends in higher education and instructional methodologies 

• Engage with industry, professional networks and associations to enhance collaboration and knowledge sharing

• Master’s degree in Data Science, Statistics, Computer Science, or a related discipline.
• A Doctoral degree will be an advantage
• At least 5 years’ Higher Education experience in Data Science or Analytics.
• Strong knowledge of Python, R, machine learning, statistical modelling, and big data tools.
• Industry or research experience in applying data science to real-world problems.

• Ability to balance theoretical foundations with applied industry-relevant case studies.
• Strong quantitative and computational thinking.
• Ability to coordinate modules that articulate into postgraduate Data pathways.
• Engagement with professional and industry networks to keep content current.