Assistant Professor

Key Responsibilities

1. Teaching & Learning

• Deliver lectures, tutorials, and lab sessions in Business Analytics, Data Science, Statistics, and related subjects.
• Develop course materials, lesson plans, and assessments aligned with academic standards.
• Train students in analytical tools such as Python, R, SQL, Excel, Power BI, Tableau, and machine learning basics.
• Evaluate student performance and provide academic counselling.
• Guide student projects, internships, and case-study-based learning.

2. Research & Publications

• Conduct high-quality research in Business Analytics, Data Science, AI/ML applications, or related fields.
• Publish papers in reputed national and international journals.
• Participate in conferences, workshops, and research collaborations.
• Contribute to funded research proposals and consultancy projects.

3. Academic Administration

• Participate in curriculum design and continuous improvement of analytics programs.
• Serve on academic committees, boards of studies, and departmental review groups.
• Support accreditation processes (NBA, NAAC, etc.) by preparing documentation and reports.

4. Industry & Institutional Engagement

• Develop industry connections for guest lectures, collaborations, and student placement support.
• Coordinate industry-driven projects, live case studies, and training programs.
• Conduct value-added courses, FDPs, and workshops for students and faculty.

5. Mentorship & Student Development

• Provide mentorship on career development, analytical skills, and research orientation.
• Support students in competitions, hackathons, and innovation initiatives.
• Foster a positive, inclusive, and engaging learning environment.

Required Qualifications & Skills

• Master’s degree or Ph.D. in Business Analytics, Data Science, Statistics, Management, Computer Science, or related fields (as per UGC/AICTE norms).
• 2-5yrs work experience in teaching industry with Management or PGDB colleges
• Strong knowledge of analytical tools such as Python, R, SAS, SPSS, Tableau, or Power BI.
• Good understanding of machine learning, predictive modelling, business intelligence, and statistical analysis.
• Excellent communication, presentation, and academic writing skills.
• Ability to handle research projects and guide student work.