JOB OBJECTIVE
To facilitate quality learning through teaching, administration and academic advisory work and ensure an outstanding student learning experience.
DUTIES AND RESPONSIBILITIES:

Teach and facilitate learning at both undergraduate and postgraduate
levels through lectures, seminars, workshops, tutorials and other learning situations as assigned by the CoD from time to time.
Participate in the development, administration and marking of exams, assignments and continuous assessments tests.
Assist in the development of learning materials, preparing schemes of work and maintaining records to monitor student progress, Achievement and attendance.
Provide advice, guidance and feedback to students to support their academic progress and referring student to support services as appropriate.
Contribute to the development, planning and implementation of high quality curriculum.
Participate in supervision and assisting of undergraduate and post graduate students in their research work.
Carry out research and produce publications, as well as other research outputs, in line with personal objectives agreed in the Faculty Annual Assessment Review (FAAR)
Participate in writing of research proposals and applying of research grants.
Contribute and participate in the development in the departmental and faculty seminars aimed at sharing research outcomes and building interdisciplinary collaboration within and outside the department.
Develop and apply innovative and appropriate learning techniques and material which create interest, understanding and enthusiasm amongst students;
Contribute to departmental, faculty and/or University wide working groups or committee as, when requested to do so;
Undertake continuous professional development and participate in staff development and training activities to update and enhance skills;
Maintain proper records of students’ examination, assignments and continuous assessments tests and ensure they are keyed in examination records management system in time;
Attend departmental, Faculty and University-wide meetings with other staff members;

QUALIFICATIONS AND EXPERIENCE

Master’s degree in computer science/ data science/ actuarial science/ information technology/ information systems or related field
At least 3 years’ teaching experience in data science and/or artificial intelligence at university level
Experience in curriculum development and reviews
PhD Degree in Computer Science/ Data Science/ Actuarial Science/ Information Technology/ Information Systems or a relevant field will be an added advantage.
Candidates with a PhD degree should have published at least 2 peer reviewed articles in distinguished academic journals.

OTHER SKILLS AND COMPETENCIES

Strong verbal and written communication skills
Excellent presentation skills
Excellent research skills
Critical thinking skills
Time management skills and attention to detail