The ideal candidate for a full-time Assistant Professor position in Analytics should have experience or a strong interest in analytics, including visualization, data mining, multivariate methods and supply chain analytics. Proficiency in programming languages commonly used in analytics such as Python or R, along with a solid understanding of machine learning techniques and their applications in business decision-making is also required. Preference will be given to candidates with a clear commitment to research, particularly in the areas of applied analytics, data-driven decision-making, supply chain analytics and emerging technologies. A dedication to the continuous improvement of teaching and course content at both the undergraduate and graduate levels is also highly valued. Applicants must hold a Ph.D. or be near completion in a relevant field and demonstrate the potential to publish in high-quality, peer-reviewed journals. Additionally, candidates should have a strong ability to collaborate with industry partners and engage in interdisciplinary research that bridges academia and business challenges. We are interested in candidates with: 1. A Ph.D., either completed or near completion, in Information Systems, Business Administration, Industrial Engineering, Systems Engineering, Economics, or another relevant field. 2. A desire and aptitude to contribute to a successful and fast-growing educational organization. 3. Potential for research and publication in international peer-reviewed journals. 4. An ability to contribute to different undergraduate and postgraduate programs. Applications should include: 1. Cover letter explaining motivation. 2. Curriculum vitae. 3. Statement of teaching, including course evaluations (if applicable). 4. Statement of research. 5. Copy of two recent working papers/published. 6. Two confidential letters of reference.