Assistant Professor of Business Analytics

Roles and responsibilities

The College of Business Administration (CBA) at Ajman University, has an opening for the position of Assistant Professor of Business Analytics, starting in Fall 2025. The selected candidate will have primary teaching and research interests in Business Analytics and will be expected to teach in graduate and undergraduate programs. The selected candidate will also be expected to actively engage with the business community. Preference will be given to candidates experienced with capstone analytics courses that engage students with industry partners to work on real-world business problems. The College of Business Administration is accredited by AACSB.

QUALIFICATIONS & EXPERIENCE:

• Ph.D. in Business Analytics or related fields (Management Science, Operations Management, Industrial Engineering, Information Systems) obtained from a reputable university, preferably an internationally ranked institution that is also accredited by AACSB
• Two or more years of teaching experience in an internationally reputable university, preferably accredited by AACSB
• Demonstrable record of excellence in developing and teaching (but not limited to) business/data analytics, software applications for business in optimization, business intelligence, and related courses at both the undergraduate and graduate levels
• Outstanding record of research and peer-reviewed publications in top-tier analytics, operations, and management journals
• Record of collaborative and interdisciplinary research would be an advantage
• Demonstrable record of supervising student projects and dissertations
• Excellent record in professional and community service
  

ESSENTIAL DUTIES & RESPONSIBILITIES:

• Design, deliver and assess graduate and undergraduate courses in Business Analytics, Business Intellighence, Operations Management and related areas
• Engage in innovative and technology-based approaches to teaching and learning
• Provide academic advising services to students
• Conduct high quality research and publish research outcomes in reputable journals and conferences
• Participate in committee and other service tasks at the department, college and/or university levels as assigned
• Actively engage in promoting the growth and visibility of Ajman University
• Provide consultancy and other industry-facing services to Ajman University partners and members of the business community
• Actively seek out methods, procedures and resources to best achieve course and lesson objectives
• Perform miscellaneous job-related duties as assigned
  

APPLICATION PROCESS

A completed application will include:

• A letter of interest addressing qualifications for the position.
• A current curriculum vitae.
• A statement of teaching and research philosophy.
• Copies of transcripts of doctoral (or other highest, as applicable) coursework.
• A list of three professional references with names, titles, phone numbers, and email addresses- including a current or previous supervisor

Desired candidate profile

Expertise in Business Analytics

• Data Analytics: Expertise in analyzing large datasets to extract meaningful insights that can guide business decision-making. This includes proficiency in techniques such as regression analysis, cluster analysis, time-series forecasting, and multivariate analysis.
• Business Intelligence (BI): Knowledge of business intelligence tools and methodologies that help businesses make data-driven decisions, including proficiency with software like Tableau, Power BI, or SAS.
• Predictive Analytics: Applying statistical models and machine learning algorithms (e.g., regression models, decision trees, neural networks) to predict future trends and behaviors in areas such as sales forecasting, customer segmentation, and market analysis.
• Optimization: Using optimization techniques, such as linear programming, integer programming, and simulation, to help businesses improve their operations, such as inventory management, supply chain, and resource allocation.
• Big Data Analytics: Proficiency in analyzing large and complex datasets using tools such as Hadoop, Spark, or cloud-based analytics platforms, as well as understanding how to extract actionable insights from big data.
• Data Visualization: Ability to use data visualization techniques and tools to communicate insights clearly to non-technical stakeholders, helping them make informed decisions.

2. Teaching and Curriculum Development

• Course Design: Developing and teaching undergraduate and graduate-level courses in business analytics, including topics like data analysis, machine learning for business, data visualization, and optimization. Courses may also cover business decision-making frameworks and how analytics can support strategic decisions.
• Hands-on Learning: Incorporating practical, hands-on experiences through case studies, data-driven projects, or using software tools like R, Python, Excel, and analytics platforms to help students understand real-world business applications.
• Active Learning: Implementing interactive teaching methods such as group projects, simulations, and business case competitions to enhance student engagement and develop their problem-solving abilities.
• Assessment and Feedback: Designing assessments (e.g., assignments, exams, projects) to measure student understanding of key concepts in business analytics, providing feedback that helps students improve their analytical skills and thinking.

3. Research and Scholarly Activity

• Applied Research: Conducting original research in business analytics, focusing on the application of data analytics, machine learning, artificial intelligence, or optimization techniques to solve real business problems. This can include research in areas like supply chain analytics, marketing analytics, financial analytics, or operations management.
• Industry Collaboration: Collaborating with businesses and industry partners to conduct research that addresses real-world challenges, such as improving business processes, enhancing customer experience, or optimizing decision-making in uncertain environments.
• Publications: Publishing research in reputable academic journals and presenting findings at conferences to contribute to the academic field of business analytics. Research may be applied or theoretical, exploring new analytical techniques or business applications.
• Grant Writing: Writing and securing research grants from government agencies, industry partners, or academic institutions to fund research projects related to business analytics.

4. Student Mentorship and Supervision

• Graduate Supervision: Mentoring graduate students (Master’s and Ph.D.) on their research projects, theses, or dissertations in business analytics. This includes providing guidance on research design, data analysis techniques, and how to apply analytics to business problems.
• Undergraduate Advising: Advising undergraduate students on academic and career paths in business analytics, helping them choose courses, internships, and research opportunities that align with their professional goals.
• Career Development: Helping students explore career opportunities in business analytics, such as roles in data science, business intelligence, operations research, and consulting. This might include guiding students on job placement, networking, and industry engagement.

5. Industry Engagement and Applied Projects

• Consulting and Advisory: Offering consulting services or collaborating with companies in the private or public sectors to apply business analytics methods to specific business problems. This could include analyzing company data to identify inefficiencies, opportunities for cost reduction, or strategies for improving customer engagement.
• Capstone Projects and Internships: Organizing capstone projects and internships where students can work on real business problems, applying analytical techniques to provide actionable solutions for companies or organizations.
• Corporate Partnerships: Building relationships with businesses and industry leaders to create opportunities for students, including internships, research collaboration, and access to real-world data for teaching and research.