Assistant Professor
1 week ago
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.
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