Visiting Faculty for the Course : Data Analytics for Retail Decision-Making, MBA

Visiting Faculty for the MBA Technology Management Program

Position Title : Visiting Faculty

Course :

Data Analytics for Retail Decision-Making, MBA

Location :

Yelahanka, Bangalore, Karnataka

Mode :

On Campus, no online classes

Duration :

One Term of a Trimester (extendable based on academic needs and performance)

20th October 2025 to 31st December 2025

Course Overview

The course “Data Analytics for Retail Decision-Making” is designed to equip MBA and postgraduate management students with analytical tools and data-driven approaches for solving real-world retail business problems. It focuses on developing the ability to interpret, model, and leverage data for improving decisions in areas such as customer management, pricing, inventory, promotion, and supply chain optimization.

Key thematic areas include :

Fundamentals of data analytics in the retail context

Retail data collection, preparation, and visualization

Predictive modeling for sales forecasting and demand estimation

Customer segmentation and recommendation systems

Pricing, promotion, and assortment optimization using data analytics

Application of AI / ML tools in retail strategy

Ethical and privacy considerations in retail data analytics

Key Responsibilities

Design and deliver lectures, tutorials, and hands-on sessions on AI / ML concepts and applications

Integrate

business and management context

into technical topics to suit MBA and postgraduate students

Develop case studies, datasets, and simulation-based exercises

Mentor students on AI / ML projects and practical applications

Collaborate with TAPMI faculty on course design, assessment, and AACSB / AoL requirements

Contribute to guest lectures, workshops, and research / consulting initiatives related to data-driven decision-making

Qualifications

Essential :

Master’s degree or Ph.D. in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Statistics, or a closely related field

Demonstrated expertise in AI / ML, with teaching or corporate training experience

Proficiency in Python, R, or equivalent programming environments for machine learning

Desirable :

Industry or research experience in retail analytics, marketing analytics, or consumer insights

Familiarity with AI / ML applications and optimization techniques in retail contexts

Record of applied research, consulting, or publications in analytics-driven retail strategy

Skills and Competencies

Ability to simplify complex technical concepts for management students

Strong communication and classroom engagement skills

Ability to bridge theory with real-world applications

Collaborative mindset and commitment to academic excellence

Remuneration

Compensation will be

commensurate with qualifications, experience, and profile

, and in line with TAPMI’s norms for visiting faculty.

Application Process

Interested candidates may send their applications to

Prof. Deepak A S (deepak.as@manipal.edu), Analytics Area Chair,

with the subject line :

“Application – Visiting Faculty (Data Analytics for Retail Decision-Making)”

The application should include :

Detailed CV (with academic, teaching, and industry experience)

List of two professional references