Pune Institute of Business Management
Website:
pibm.in
Job details:
PIBM – PUNE INSTITUTE OF BUSINESS MANAGEMENT
Teaching Faculty – MBA/PGDM (Business Analytics & Artificial Intelligence)
Department
MBA – Business Analytics & Artificial Intelligence
Reporting To
Head of Department (HoD) – BA & AI
Position Type
Assistant Professor (Full Time)
Location
Pune, Maharashtra
Experience Required
Minimum 2 Years (Teaching / Industry / Research)
Qualification
MBA / M.Sc. / M.Tech + PhD preferred (as per AICTE norms)
1.About PIBM
Pune Institute of Business Management (PIBM) is a leading MBA institution in Pune committed to delivering industry-aligned management education. The MBA programme in Business Analytics & Artificial Intelligence is designed to produce data-driven decision-makers equipped with quantitative skills, analytical thinking, and a strong command over AI-powered business tools.
2.Role Summary
The Faculty Member will be responsible for delivering high-quality, outcome-based instruction in one or more core subjects within the MBA BA & AI programme. The incumbent is expected to bridge theoretical rigour — particularly in Mathematics and Statistics — with practical, industry-relevant applications in analytics, machine learning, and AI-driven business strategy.
3.Key Responsibilities
A. Teaching & Curriculum Delivery
- Plan, prepare, and deliver engaging lectures for MBA students across subjects such as Business Statistics, Applied Mathematics, Predictive Analytics, Machine Learning for Business, Data Visualisation, and AI Strategy.
- Design course plans, session notes, case studies, assignments, and examination papers in accordance with AICTE/university guidelines.
- Integrate real-world datasets and business use cases to demonstrate the applied value of mathematical and statistical concepts.
- Adopt outcome-based education (OBE) frameworks, blended learning models, and flipped classroom techniques to maximise student engagement.
- Use analytical tools including Python, R, SQL, Tableau, Power BI, and/or MS Excel to deliver hands-on, tool-driven sessions.
B. Assessment & Student Development
- Conduct formative and summative assessments; evaluate assignments, projects, and examinations objectively and on schedule.
- Mentor and guide students on live projects, capstone assignments, dissertation work, and industry-sponsored analytics challenges.
- Provide constructive feedback to improve students' quantitative reasoning, statistical interpretation, and analytical communication skills.
- Identify students requiring academic support and coordinate remedial or enrichment interventions.
C. Research & Academic Contribution
- Contribute to the department's research output through publications in peer-reviewed journals, conference presentations, or working papers.
- Pursue and support funded research, consultancy projects, or industry collaborations aligned with analytics and AI.
- Stay current with emerging developments in Generative AI, Large Language Models (LLMs), Deep Learning, and their business implications.
- Participate in curriculum review committees and assist the HoD in developing new electives or certifications.
D. Institutional & Administrative Duties
- Participate actively in faculty meetings, departmental workshops, seminars, and industry-academia events.
- Support student activities such as Analytics Hackathons, AI Summits, Data Case Competitions, and industry visits.
- Assist in accreditation and NBA/NAAC/AICTE documentation where applicable.
- Uphold the institution's academic standards, code of conduct, and professional ethics at all times.
4.Subject Areas (Indicative, Not Exhaustive)
Candidates should be equipped to teach in one or more of the following areas:
Quantitative & Analytical Foundations
AI, ML & Technology Applications
Business Mathematics & Quantitative Methods
Machine Learning for Business
Business Statistics & Probability
Deep Learning & Neural Networks (Applied)
Statistical Inference & Hypothesis Testing
Natural Language Processing (NLP) for Business
Regression & Multivariate Analysis
Generative AI & Prompt Engineering
Operations Research & Linear Programming
AI Strategy & Responsible AI
Predictive & Prescriptive Analytics
Big Data Analytics & Cloud Platforms
Data Visualisation (Tableau / Power BI)
Python / R for Data Science
Business Intelligence & SQL
Capstone / Live Analytics Projects
5.Educational Qualifications
- Minimum: MBA / M.Sc. (Statistics / Mathematics / Data Science / Computer Science) / M.Tech with first class or equivalent, from a recognised institution.
- Preferred: Ph.D. in a relevant discipline (Management, Statistics, Mathematics, Computer Science, Data Science, or AI) as per AICTE / UGC norms.
- UGC-NET / SET qualification is an added advantage for candidates without a Ph.D.
- Certifications in Data Science, AI/ML, or Analytics (e.g., AWS, Google Cloud, Coursera/edX specialisations) will be considered favourably.
- Strong academic record throughout — a minimum of 60% or equivalent CGPA at the qualifying degree level.
6.Experience Requirements
Minimum
3 years of experience in academia (teaching at MBA/PG level) and/or industry (data analytics, AI/ML, business intelligence, consulting, or related fields).
Preferred
3–7 years of combined teaching and/or industry experience, with documented contributions to research, curriculum design, or industry projects in analytics/AI.
7.Technical Competencies & Key Skills
Core Quantitative Skills (Essential)
- Mathematics: Strong command of linear algebra, calculus, optimisation, and discrete mathematics as applicable to analytics and ML.
- Statistics: Proficiency in descriptive statistics, inferential statistics, probability distributions, hypothesis testing, Bayesian methods, regression analysis, and time series analysis.
- Quantitative Methods: Expertise in operations research, decision analysis, linear/non-linear programming, and simulation modelling.
- Research Methods: Ability to design, execute, and present quantitative and qualitative research.
Programming & Analytics Tools (Highly Desirable)
- Programming: Python (NumPy, Pandas, Scikit-learn, TensorFlow/PyTorch) and/or R for statistical computing and ML model development.
- Databases & SQL: Proficiency in relational databases, SQL querying, and big data frameworks (Spark, Hive – advantageous).
- Visualisation Tools: Hands-on experience with Tableau, Power BI, and/or Google Data Studio.
- Cloud & Big Data Platforms: Familiarity with AWS, Google Cloud Platform (GCP), or Microsoft Azure analytics services.
- Spreadsheet Analytics: Advanced Microsoft Excel (including Solver, PivotTables, and macros).
Pedagogical & Soft Skills
- Excellent verbal and written communication skills in English; ability to translate complex quantitative concepts into accessible business narratives.
- Proficiency in designing case studies, simulations, and live projects rooted in industry data and real-world business problems.
- Familiarity with Learning Management Systems (LMS) such as Moodle, Blackboard, or similar platforms.
- Collaborative mindset with the ability to work cross-functionally with industry partners, placement teams, and other faculty.
8.Desirable Attributes
- Prior experience of teaching at MBA / PGDM level at AICTE-approved institutions.
- Published research in ABDC/SCOPUS/UGC-CARE-listed journals in quantitative management, data science, or AI.
- Industry exposure in roles such as Data Analyst, Data Scientist, Business Intelligence Analyst, AI/ML Engineer, Strategy Consultant, or similar.
- Experience building industry collaborations, MOUs, or sponsored research projects.
- Knowledge of ethical AI frameworks, data privacy regulations (PDPB / GDPR), and responsible AI governance.
- Familiarity with global benchmark programmes (IIM Calcutta PGDBA, IIM Bangalore PGPBA, ISB Analytics courses) and ability to align course design to those standards.
9.Key Performance Indicators (KPIs)
- Student feedback score (minimum threshold as defined by the institution annually).
- Course completion and assessment delivery within stipulated timelines.
- Research output: at least one publication or conference paper per academic year (for full-time roles).
- Active participation in at least two departmental or cross-functional initiatives per semester.
- Student placement contribution: engagement with corporate connect, industry mentorship, or pre-placement training activities.
Click on Apply to know more.