Visiting faculty for the course: data analytics for retail decision-making, mba

6 days ago

Kochi, India TAPMI Bengaluru Full time

Visiting Faculty for the MBA Technology Management ProgramPosition Title:Visiting FacultyCourse:Data Analytics for Retail Decision-Making, MBALocation:Yelahanka, Bangalore, KarnatakaMode: On Campus, no online classesDuration:One Term of a Trimester (extendable based on academic needs and performance)20th October 2025 to 31st December 2025Course OverviewThe 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 contextRetail data collection, preparation, and visualizationPredictive modeling for sales forecasting and demand estimationCustomer segmentation and recommendation systemsPricing, promotion, and assortment optimization using data analyticsApplication of AI/ML tools in retail strategyEthical and privacy considerations in retail data analyticsKey ResponsibilitiesDesign and deliver lectures, tutorials, and hands-on sessions on AI/ML concepts and applicationsIntegrate business and management context into technical topics to suit MBA and postgraduate studentsDevelop case studies, datasets, and simulation-based exercisesMentor students on AI/ML projects and practical applicationsCollaborate with TAPMI faculty on course design, assessment, and AACSB/Ao L requirementsContribute to guest lectures, workshops, and research/consulting initiatives related to data-driven decision-makingQualificationsEssential:Master’s degree or Ph. D. in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Statistics, or a closely related fieldDemonstrated expertise in AI/ML, with teaching or corporate training experienceProficiency in Python, R, or equivalent programming environments for machine learningDesirable:Industry or research experience in retail analytics, marketing analytics, or consumer insightsFamiliarity with AI/ML applications and optimization techniques in retail contextsRecord of applied research, consulting, or publications in analytics-driven retail strategySkills and CompetenciesAbility to simplify complex technical concepts for management studentsStrong communication and classroom engagement skillsAbility to bridge theory with real-world applicationsCollaborative mindset and commitment to academic excellenceRemunerationCompensation will be commensurate with qualifications, experience, and profile, and in line with TAPMI’s norms for visiting faculty.Application ProcessInterested candidates may send their applications to Prof. Deepak A S ( ), 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

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