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

4 weeks ago

Kakinada, India TAPMI Bengaluru Full time

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

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