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.