Marketing Technology & Customer Analytics Faculty

Qualifications

• Applicants must hold a PhD in Marketing or a closely related discipline, with a strong analytical and technology-oriented specialization, obtained from a university ranked within the top 500 in the QS World University Rankings
• Candidates should demonstrate a strong record of teaching effectiveness, research productivity, and engagement with industry and/or professional communities
• Evidence of publications in reputable, Scopus-indexed journals is expected, commensurate with academic rank
• Relevant professional certifications are preferred
• Expertise and Technical Competencies: Candidates should demonstrate expertise in areas including: Customer relationship management and customer intelligence Customer analytics Marketing technology (MarTech) Marketing automation E-commerce analytics Digital experimentation Customer experience analytics Digital marketing analytics Customer journey and engagement analytics Retail and omnichannel analytics Proficiency in analytical and programming tools such as Python and/or R, together with data visualization and business intelligence platforms such as Power BI and/or Tableau, is highly desirable
• Experience with advanced analytical techniques such as text mining, image analytics, topic modelling, clustering, social-network analysis, machine learning, and business intelligence/data visualization is also highly desirable, given the analytical and technical content of the MScDMA curriculum
• Experience

Requirements

• Candidates should demonstrate relevant university-level teaching experience appropriate to the academic rank applied for, together with evidence of contribution to curriculum development, student supervision, and academic service
• Candidates applying at the Associate Professor level should additionally demonstrate appropriate experience in undergraduate and graduate teaching and postgraduate supervision, commensurate with the requirements of the academic rank
• Experience with curriculum development, supervision of graduation projects and/or postgraduate research, and familiarity with AACSB accreditation processes would be advantageous
• Teaching Areas: Teaching will span key areas of Digital Marketing and Analytics, including: Digital marketing strategy and planning Customer relationship management and customer analytics Customer intelligence Marketing technology and marketing automation E-commerce and digital consumer behaviour Customer experience and customer journey analytics Digital experimentation Social media and influencer analytics Retail and omnichannel analytics Brand management Marketing research and data-driven decision making Ethics and responsible use of technology and consumer data Research Focus: Successful candidates will be expected to maintain an active research agenda and publish in reputable, peer-reviewed journals, with research expectations commensurate with academic rank and CUD requirements
• Relevant research areas may include customer analytics and intelligence, CRM, marketing technology, marketing automation, digital consumer behaviour, customer experience, e-commerce, digital experimentation, social media analytics, omnichannel strategy, and the responsible use of customer data and technology in marketing
• Candidates are also expected to engage with industry and professional communities to strengthen applied research, knowledge exchange, and professional practice

Key Responsibilities

• Serve as subject matter experts, supporting the Program Chair or Coordinator in academic operations and helping ensure curriculum alignment with CUD requirements, industry needs, and current developments in the discipline
• Teach undergraduate and graduate courses within their respective areas of expertise, ensuring engaging delivery, current course content, updated syllabi, and timely assessment and grading
• Maintain accurate student records, hold regular office hours, provide academic support, and advise students as required
• Recommend appropriate learning resources, technologies, and materials to enhance the student learning experience
• Supervise independent studies, student projects, internships, graduation projects, and postgraduate research, as appropriate to academic rank
• Contribute to curriculum evaluation, course development, and the continuous improvement of academic programs
• Conduct high-quality research, publish in reputable peer-reviewed journals, and maintain active professional and scholarly engagement
• Participate in academic governance, faculty and departmental meetings, accreditation processes, and related academic documentation
• Contribute to the School of Management's accreditation activities, including AACSB-related initiatives where applicable
• Support academic administrative activities, including student advising, registration, and orientation activities as required
• Engage in community outreach, industry collaborations, knowledge exchange, and professional service
• Represent CUD at professional events, conferences, and relevant public engagements
• Participate in professional development and other capacity-building initiatives
• Our eligible faculty employees enjoy competitive compensation and benefits, including: Generous academic annual leave

Desired Candidate Profile

Applicants must hold a PhD in Marketing or a closely related discipline, with a strong analytical and technology-oriented specialization, obtained from a university ranked within the top 500 in the QS World University Rankings. Candidates should demonstrate a strong record of teaching effectiveness, research productivity, and engagement with industry and/or professional communities. Evidence of publications in reputable, Scopus-indexed journals is expected, commensurate with academic rank. Relevant professional certifications are preferred. Expertise and Technical Competencies: Candidates should demonstrate expertise in areas including: Customer relationship management and customer intelligence Customer analytics Marketing technology (MarTech) Marketing automation E-commerce analytics Digital experimentation Customer experience analytics Digital marketing analytics Customer journey and engagement analytics Retail and omnichannel analytics Proficiency in analytical and programming tools such as Python and/or R, together with data visualization and business intelligence platforms such as Power BI and/or Tableau, is highly desirable. Experience with advanced analytical techniques such as text mining, image analytics, topic modelling, clustering, social-network analysis, machine learning, and business intelligence/data visualization is also highly desirable, given the analytical and technical content of the MScDMA curriculum. Experience

Requirements

• Candidates should demonstrate relevant university-level teaching experience appropriate to the academic rank applied for, together with evidence of contribution to curriculum development, student supervision, and academic service
• Candidates applying at the Associate Professor level should additionally demonstrate appropriate experience in undergraduate and graduate teaching and postgraduate supervision, commensurate with the requirements of the academic rank
• Experience with curriculum development, supervision of graduation projects and/or postgraduate research, and familiarity with AACSB accreditation processes would be advantageous