ABOUT THE POSITION

The Master of Data Analytics program invites applications for the position, Assistant Professor, Master of Data Analytics. We are seeking highly qualified and motivated individuals with a strong background in math, computer science, economics, information technology or related fields to join our diverse faculty team. The ideal candidate will have an advanced academic background (PhD) and extensive expertise in the fields of data science, machine learning, and data analytics. The candidate will be responsible to teach courses in operations analytics, prescriptive analytics and advanced data analytics, as well as mentoring students to achieve career success.

REQUIRED QUALIFICATIONS AND EXPERIENCE:

• PhD in Industrial Engineering, Mathematics or Operations Research.
• Strong knowledge of machine learning techniques and algorithms.
• Expertise in Optimization techniques, Optimization software and python libraries, ERP systems such as Oracle or SAP is a plus.
• Proficiency in at least two of the following software tools: SAS, R, SQL, Python.
• Strong understanding of data analytics and data modeling techniques.
• Previous teaching experience at the university level, with a track record of successfully engaging and inspiring students.
• Previous experience in a research or industry-based data science role is preferred.
• Strong research profile in supply chain optimization, operations management, and data analytics.

• Design and deliver comprehensive and engaging lectures on data science topics, covering areas such as machine learning, statistical analysis, and data modeling techniques.
• Develop teaching plans, notes, and instructional materials to support effective learning.
• Ability to teach students key concepts in predictive, prescriptive, and descriptive analysis.
• Develop, supervise, and grade assignments, exams, and student projects.
• Monitor student attendance, academic progress, and provide feedback on performance.
• Provide academic counseling and career mentorship to support student’s growth and success.
• Actively participate in curriculum development and continuous improvement of course content.
• Collaborate with other faculty members on research initiatives and interdisciplinary projects.
• Stay current with trends and advancements in data science and related fields, and integrate this knowledge into course materials.
• Foster a motivating, student-centered learning environment.
• Encourage critical thinking and problem-solving amongst students in the application of data science concepts.