About the Role:
We are looking for a passionate Data Scientist with a strong background in Operations Research (OR) and Supply Chain Analytics to join our Data Science & AI team. The ideal candidate will leverage data-driven modeling, optimization, and simulation to enhance operational efficiency and drive innovation across functions such as flight operations, crew management, ground operations, maintenance, and supply chain.
You will collaborate with domain experts, data engineers, and business teams to conduct applied research, prototype advanced analytical models, and translate insights into scalable solutions that make measurable impact on our operational performance.
Key Responsibilities:
Research & Problem Formulation
o Identify opportunities for operational improvements and formulate research problems across different airline functions (e.g., crew rostering, maintenance scheduling, spare parts management, network planning, etc.).
o Explore optimization, forecasting, and simulation techniques to support strategic and tactical decision-making.
Model Development
o Build and validate mathematical optimization, simulation, and machine learning models for real-world airline operations problems.
o Develop what-if analysis frameworks to test scenarios and assess operational trade-offs.
Data Science & Analytics
o Work with large, complex datasets to derive actionable insights using advanced statistical and analytical techniques.
o Integrate OR techniques (linear/non-linear optimization, mixed-integer programming, queuing models, stochastic modeling) with ML-based forecasting.
Implementation & Collaboration
o Partner with engineering and product teams to operationalize models and embed them into decision-support systems.
o Collaborate with business stakeholders to ensure models and recommendations are interpretable, practical, and aligned with operational goals.
Continuous Research & Innovation
o Stay current with academic and industry trends in operations research, AI in aviation, and supply chain optimization.
o Publish internal whitepapers or PoC studies demonstrating new methods for efficiency improvement.
Required Skills & Qualifications:
Bachelor’s or Master’s degree in Operations Research, Industrial Engineering, Applied Mathematics, Statistics, Computer Science, or a related field from IISc/IITs/BITS Pilani only.
2–5 years of experience applying operations research and data science techniques to real-world business problems.
Strong command over optimization tools and solvers
Hands-on experience with Python, SQL, and data analysis libraries (Pandas, NumPy, SciPy, scikit-learn).
Knowledge of forecasting, simulation, and statistical modeling.
Experience working with large-scale data systems
Strong analytical thinking, problem structuring, and business acumen.
Excellent communication skills — ability to explain complex concepts to non-technical stakeholders.
Preferred Qualifications (Good to Have):
Experience in the aviation industry (network planning, scheduling, crew or maintenance optimization, etc.).
Experience working on research or innovation projects involving experimentation and model benchspaning.
Familiarity with cloud platforms (Azure, GCP, or AWS) for model deployment.
Why Join Us:
- Opportunity to work at the intersection of data science, operations research, and aviation— solving problems that impact millions of passengers.
- Collaborate with a multidisciplinary team driving innovation in airline operations.
- Be part of research initiatives shaping the next generation of intelligent operational systems
At IndiGo, we believe in the innate strength of an energetic, diverse, and inclusive workforce, where the viewpoints and life experiences of our employees help us foster strong connection with all our customers. Our diversity equity and inclusion efforts are designed to attract, nurture, and advance the lives of our employees and customers irrespective of their, but not limited to, gender, race, color, religion, caste, creed, ethnicity, origin, language, social and economic status, sexual orientation, persons with disabilities, nationality, age, marital and maternity status.
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