Data Scientist - Machine Learning

United Airlines India Knowledge Center; Gurugram District; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

United Airlines India Knowledge Center invites a Data Scientist to design, build, and deploy scalable AI and Generative AI solutions that enhance customer experiences and business efficiency across our network.

You will work with Python, SQL, LLMs, RAG, and agentic AI frameworks to translate complex business needs into reliable, observable AI capabilities, collaborating with cross‑functional teams to communicate findings and recommendations.

Qualifications

• Master’s or Ph.D. degree.
• Data Science, Statistics, Engineering, Computer Science, Operations Research, or a related STEM field.
• 4–7+ years of industry experience in AI engineering, data science, machine learning, or applied advanced analytics, including production model deployment.
• Advanced proficiency in Python and SQL, with software engineering best practices including object‑oriented programming, Git, and CI/CD; experience architecting data pipelines and working with large datasets in relational or distributed databases such as Snowflake, BigQuery, SQL Server, or Teradata; deep expertise in Generative AI, including prompt engineering, LLM fine‑tuning, embeddings, RAG, vector databases, and Agentic AI frameworks; hands‑on MLOps or LLMOps experience covering model monitoring, latency management, drift mitigation, and system reliability;
• Fluent in written and spoken English.

Responsibilities

• The Data Scientist designs, develops, and implements scalable AI and Generative AI solutions that improve customer experience, business efficiency, and decision-making.
• The role builds production‑grade applications and workflows using Python, SQL, large language models, Retrieval‑Augmented Generation, and agentic AI frameworks.
• It applies advanced analysis, prompt engineering, evaluation, and observability practices to deliver reliable and useful AI capabilities.
• The role partners with cross‑functional teams to translate ambiguous business needs into practical solutions and clearly communicate findings and recommendations.

Skills

Python

SQL

LLM

MLOps

Data pipelines

English fluency

Git

CI/CD

Education

Master’s or Ph.D.

STEM fields (Data Science/Statistics/Engineering/CS/OR)

Tools

Snowflake

BigQuery

SQL Server

Teradata

Job description

Achieving our goals starts with supporting yours. Grow your career, access top-tier health and wellness benefits, build lasting connections with your team and our customers, and travel the world using our extensive route network.

Come join us to create what’s next. Let’s define tomorrow, together.

Description

Job overview and responsibilities

The Data Scientist designs, develops, and implements scalable AI and Generative AI solutions that improve customer experience, business efficiency, and decision-making. The role builds production‑grade applications and workflows using Python, SQL, large language models, Retrieval‑Augmented Generation, and agentic AI frameworks. It applies advanced analysis, prompt engineering, evaluation, and observability practices to deliver reliable and useful AI capabilities. The role partners with cross‑functional teams to translate ambiguous business needs into practical solutions and clearly communicate findings and recommendations.

This position is offered on local terms and conditions. Expatriate assignments and sponsorship for employment visas, even on a time‑limited visa status, will not be awarded.

Qualifications

What’s needed to succeed (Minimum Qualifications)

• Master’s or Ph.D. degree.
• Data Science, Statistics, Engineering, Computer Science, Operations Research, or a related STEM field.
• 4–7+ years of industry experience in AI engineering, data science, machine learning, or applied advanced analytics, including production model deployment.
• Advanced proficiency in Python and SQL, with software engineering best practices including object‑oriented programming, Git, and CI/CD; experience architecting data pipelines and working with large datasets in relational or distributed databases such as Snowflake, BigQuery, SQL Server, or Teradata; deep expertise in Generative AI, including prompt engineering, LLM fine‑tuning, embeddings, RAG, vector databases, and Agentic AI frameworks; hands‑on MLOps or LLMOps experience covering model monitoring, latency management, drift mitigation, and system reliability;
• Fluent in written and spoken English.

What will help you propel from the pack (Preferred Qualifications)

• Advanced coursework or specialization in machine learning, artificial intelligence, applied statistics, or cloud computing.
• Experience deploying and scaling enterprise Generative AI applications, particularly multi‑agent frameworks or enterprise‑scale Retrieval‑Augmented Generation.
• Relevant cloud, machine learning, or MLOps certification.