IndiGo is Hiring Data Analyst (Data Science/ML) | Gurgaon

Job Description

IndiGo's listing — for India's largest airline by market share — is a genuinely distinctive opportunity to apply 𝐝𝐚𝐭𝐚 𝐬𝐜𝐢𝐞𝐧𝐜𝐞 𝐚𝐧𝐝 𝐦𝐚𝐜𝐡𝐢𝐧𝐞 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠 to aviation operations, though there's a real ambiguity worth flagging: the posting states "Relevant experience in Data Science, Machine Learning, or Advanced Analytics" as a qualification without specifying years, and doesn't include fresher-specific framing anywhere in the text. Combined with the technically demanding skill list (production ML deployment, MLOps, Databricks/Snowflake/cloud platforms), this may not be genuinely fresher-accessible despite appearing on job boards without an explicit experience floor — worth confirming directly with IndiGo's recruiting team where this actually sits on the experience spectrum.

𝐓𝐡𝐞 𝐚𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐝𝐞𝐚𝐝𝐥𝐢𝐧𝐞 𝐢𝐬 𝐧𝐨𝐭𝐚𝐛𝐥𝐲 𝐜𝐥𝐨𝐬𝐞 — August 31, 2026, meaning very limited time remains to apply as of this posting. If IndiGo is of interest, don't delay.

The role's real scope is genuinely comprehensive 𝐞𝐧𝐝-𝐭𝐨-𝐞𝐧𝐝 𝐝𝐚𝐭𝐚 𝐬𝐜𝐢𝐞𝐧𝐜𝐞 𝐰𝐨𝐫𝐤 — from translating business problems into ML solutions, through feature engineering and model building, to production deployment and monitoring. This is meaningfully more advanced than typical entry-level "data analyst" work, requiring not just modeling skills but also 𝐌𝐋𝐎𝐩𝐬/𝐝𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 𝐜𝐨𝐦𝐩𝐞𝐭𝐞𝐧𝐜𝐲, which is a specialized skill even among data scientists with a few years of experience.

𝐎𝐮𝐫 𝐓𝐚𝐤𝐞:

- 𝐆𝐨𝐨𝐝 𝐟𝐨𝐫: candidates with genuine, demonstrated experience in data science/ML (through internships, strong project portfolios, or prior work), interested in applying these skills to real airline/aviation operational problems

- 𝐍𝐨𝐭 𝐢𝐝𝐞𝐚𝐥 𝐟𝐨𝐫: true freshers without hands-on ML project experience — despite lacking an explicit years requirement, the described scope (production model deployment, MLOps) suggests real prior exposure is expected

- 𝐒𝐞𝐥𝐞𝐜𝐭𝐢𝐨𝐧 𝐝𝐢𝐟𝐟𝐢𝐜𝐮𝐥𝐭𝐲: 𝐋𝐢𝐤𝐞𝐥𝐲 𝐡𝐢𝐠𝐡 given the deployment-focused, production-oriented skill set combined with the deadline urgency limiting preparation time

- 𝐂𝐚𝐫𝐞𝐞𝐫 𝐭𝐫𝐚𝐣𝐞𝐜𝐭𝐨𝐫𝐲: could lead into Senior Data Scientist, ML Engineer, or AI Solutions Lead roles within IndiGo's growing data/analytics function, with aviation-domain data science experience being a distinctive credential for future roles in travel, logistics, or operations-focused AI work

𝐂𝐨𝐦𝐩𝐞𝐧𝐬𝐚𝐭𝐢𝐨𝐧 𝐂𝐨𝐧𝐭𝐞𝐱𝐭: IndiGo hasn't disclosed pay for this role. Data Scientist/ML roles at large Indian companies applying AI to core business operations typically range around ₹8–15 LPA depending on actual experience level, based on general market data for comparable data science roles — this is a broad estimate given the ambiguity in stated experience requirements.

𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐲: Given the imminent deadline, apply promptly if interested rather than extensively preparing first. Since the role explicitly values 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐌𝐋 𝐝𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 𝐚𝐧𝐝 𝐌𝐋𝐎𝐩𝐬 𝐞𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞 (Databricks, Snowflake, Azure/AWS all listed as preferred), lead with any project — even personal or academic — where you took a model beyond just training and into some form of deployment or productionization, since that's what distinguishes this listing from a typical entry-level analytics role.

Roles & Responsibilities

The responsibilities span the complete ML lifecycle — from business problem translation through production deployment and stakeholder communication.

- Translate business problems into data science solutions

- Analyze data, build features, and develop ML/AI models

- Deploy, monitor, and improve production models

- Communicate insights and recommendations to stakeholders

- Collaborate with data engineering, product, and business teams

Qualifications & Eligibility

No explicit years-of-experience figure is stated, though "relevant experience" is listed as a qualification — worth clarifying this ambiguity directly.

- Bachelor's/Master's in Computer Science, Statistics, Mathematics, Engineering, or related field

- Relevant experience in Data Science, Machine Learning, or Advanced Analytics

Skills Required

A genuinely comprehensive, production-oriented skill set spanning core data science and deployment infrastructure.

- Python, SQL

- Machine Learning & Statistics

- Data Analysis & Visualization

- Preferred: Deep Learning/GenAI

- Preferred: Databricks, Snowflake, Azure/AWS

- Preferred: MLOps and model deployment