Key Responsibilities:

Research &amp; Problem Formulation

<ul>
<li>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.).</li>
</ul>

<ul>
<li>Explore optimization, forecasting, and simulation techniques to support strategic and tactical decision-making.</li>
</ul>

Model Development

<ul>
<li>Build and validate mathematical optimization, simulation, and machine learning models for real-world airline operations problems.</li>
</ul>

<ul>
<li>Develop what-if analysis frameworks to test scenarios and assess operational trade-offs.</li>
</ul>

Data Science &amp; Analytics

<ul>
<li>Work with large, complex datasets to derive actionable insights using advanced statistical and analytical techniques.</li>
</ul>

<ul>
<li>Integrate OR techniques (linear/non-linear optimization, mixed-integer programming, queuing models, stochastic modeling) with ML-based forecasting.</li>
</ul>

Implementation &amp; Collaboration

<ul>
<li>Partner with engineering and product teams to operationalize models and embed them into decision-support systems.</li>
</ul>

<ul>
<li>Collaborate with business stakeholders to ensure models and recommendations are interpretable, practical, and aligned with operational goals.</li>
</ul>

Continuous Research &amp; Innovation

<ul>
<li>Stay current with academic and industry trends in operations research, AI in aviation, and supply chain optimization.</li>
</ul>

<ul>
<li>Publish internal whitepapers or PoC studies demonstrating new methods for efficiency improvement.</li>
</ul>

Required Skills &amp; Qualifications:

<ul>
<li>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.</li>
</ul>

<ul>
<li>2–5 years of experience applying operations research and data science techniques to real-world business problems.</li>
</ul>

<ul>
<li>Strong command over optimization tools and solvers</li>
</ul>

<ul>
<li>Hands-on experience with Python, SQL, and data analysis libraries (Pandas, NumPy, SciPy, scikit-learn).</li>
</ul>

<ul>
<li>Knowledge of forecasting, simulation, and statistical modeling.</li>
</ul>

<ul>
<li>Experience working with large-scale data systems</li>
</ul>

<ul>
<li>Strong analytical thinking, problem structuring, and business acumen.</li>
</ul>

<ul>
<li>Excellent communication skills — ability to explain complex concepts to non-technical stakeholders.</li>
</ul>

Preferred Qualifications (Good to Have):

<ul>
<li>Experience in the aviation industry (network planning, scheduling, crew or maintenance optimization, etc.).</li>
</ul>

<ul>
<li>Experience working on research or innovation projects involving experimentation and model benchmarking.</li>
</ul>

<ul>
<li>Familiarity with cloud platforms (Azure, GCP, or AWS) for model deployment.</li>
</ul>

Data Scientist

Key Responsibilities: Research &amp; Problem Formulation 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.). Explore optimization, forecasting, and simulation techniques to support strategic and tactical decision-making. Model Development Build and validate mathematical optimization, simulation, and machine learning models for real-world airline operations problems. Develop what-if analysis frameworks to test scenarios and assess operational trade-offs. Data Science &amp; Analytics Work with large, complex datasets to derive actionable insights using advanced statistical and analytical techniques. Integrate OR techniques (linear/non-linear optimization, mixed-integer programming, queuing models, stochastic modeling) with ML-based forecasting. Implementation &amp; Collaboration Partner with engineering and product teams to operationalize models and embed them into decision-support systems. Collaborate with business stakeholders to ensure models and recommendations are interpretable, practical, and aligned with operational goals. Continuous Research &amp; Innovation Stay current with academic and industry trends in operations research, AI in aviation, and supply chain optimization. Publish internal whitepapers or PoC studies demonstrating new methods for efficiency improvement. Required Skills &amp; 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 benchmarking. Familiarity with cloud platforms (Azure, GCP, or AWS) for model deployment.

Data Scientist in New Delhi (UID-14286)

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