Professor of Business Analytics

2 days ago

Bengaluru, Karnataka, India beBeeProfession Full time ₹ 15,00,000 - ₹ 20,00,000

Business Analytics and AI Professor Position

Dayananda Sagar University is seeking a motivated Business Analytics and AI professor to join the School of Commerce and Management Studies. The candidate will contribute to the development and delivery of cutting-edge academic programs, conduct impactful research, and support student learning in areas at the intersection of business and technology.

Key Responsibilities:

  • Teach undergraduate and postgraduate courses in areas such as Business Analytics, Machine Learning, Predictive Modeling, AI in Business, Data Visualization, and related subjects.
  • Design curriculum and course content using modern tools and platforms (e.g., Python, R, Tableau, Power BI, SQL, etc.).
  • Conduct high-quality research and publish in peer-reviewed journals.
  • Supervise student projects, internships, and capstone assignments involving real-world data problems.
  • Integrate AI and analytics applications into business problem-solving scenarios.
  • Support departmental initiatives in industry collaboration, curriculum innovation, and academic events.
  • Participate in faculty development programs, seminars, and conferences.
  • Assist in grant writing, research funding proposals, and collaborative projects.

Eligibility Criteria:

  • Ph.D. in Business Analytics, Data Science, Ai, Computer Science, or Management with a specialization in Analytics/AI is mandatory.
  • 1–3 years of relevant experience in teaching, research, or industry.
  • Demonstrated experience or academic work in areas like statistical modeling, machine learning, AI applications, or big data technologies.
  • Strong communication and interpersonal skills.
  • Knowledge of programming languages/tools such as Python, R, SQL, Power BI, Excel, and cloud-based analytics platforms.

Desirable Skills:

  • Experience with real-world datasets and live analytics projects.
  • Industry certifications (e.g., Microsoft Certified Data Analyst, Google Data Analytics, AWS for Data, etc.).
  • Ability to guide interdisciplinary research and innovation.
  • Experience in blended and experiential learning methods.
  • Active participation in academic and industry networks.

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