Lead Data Scientist

Sabre; Bengaluru; On-site; INR 2,800,000 - 5,600,000; Full time

Job summary

Sabre seeks a Data Science Engineer to join the Sabre Labs Research team, driving AI-powered solutions across airline pricing, agency automation, and network planning. You will build high-performance systems blending optimization with Generative AI and MLOps.

You will design, develop, and test software for cloud-based tools, architect complex models, and mentor junior staff in a fast-paced, publishing-minded environment.

Qualifications

• Minimum 5 years of related experience in Data Science, AI Engineering, or Operations Research.
• Advanced Degree (PhD preferred) in Mathematics, Statistics, Computer Science, or Physics with a strong research background.
• Proven experience in Agile Software Development, moving complex models from research to production.
• Expertise in Deep Learning, Reinforcement Learning, and NLP.
• High-performance programming with Python and C++ for latency-sensitive tasks.
• Strong analytical skills with real-time data from GDS/OTA and airline sources.
• Deep knowledge of Modern AI Tech Stack including GCP (Vertex AI, BigQuery), MLOps tools, and containers.

Responsibilities

• Architects, codes, and deploys complex software solutions integrating mathematical algorithms and ML models into Sabres platforms.
• Drives Research & Innovation by prototyping and scaling next-gen ideas in travel tech.
• Designs end-to-end AI systems focusing on LLMs for automated agency support and conversational commerce.
• Solves high-impact challenges by optimizing GDS workflows and migrating legacy logic to modern architectures.
• Establishes AI lifecycle policies and standards for robust model performance in volatile data landscapes.
• Promotes engineering excellence through Python and C++ to production-quality, low-latency systems.
• Collaborates with leadership to align tech roadmaps with business goals like NDC adoption and operational efficiency.
• Mentors junior data scientists and engineers, fostering rigorous experimentation and high-performance engineering.

Skills

Data Science

AI Engineering

Optimization

Python

C++

NLP

MLOps

Leadership

Education

PhD preferred in Mathematics/Statistics/CS/Physics

Tools

Docker

Kubernetes

GCP

Vertex AI

BigQuery

Git

Job description

Sabre is seeking a talented Data Science Engineer to join the Sabre Labs Research team.

Sabre Labs Research is a specialized team of researchers, mathematicians, and AI engineers who serve as the intelligent core of Sabres travel marketplace. We are dedicated to solving the most complex challenges across the global travel domain.

Our mission spans

Airline Pricing, Agency Automation, Network Planning, Airline Operations, and Departure Control Systems (DCS). We build high-performance systems that streamline travel agency workflows, optimize airline networks, and enhance the productivity of travel consultants worldwide. By blending classical mathematical optimization with cutting-edge Generative AI and robust MLOps, we ensure our models power the next generation of travel distribution from initial search and booking to post-trip service, agency efficiency, and seamless airport operations.

At Sabre, were passionate about building software that solves problems. In this role, you will plan, design, develop, and test software systems or applications for software enhancements and new products including cloud-based tools.

Role and Responsibilities:

Architects, codes, and deploys complex software solutions that integrate advanced mathematical algorithms and machine learning models into Sabres core retailing, Network Planning, Agency Automation, and Departure Control platforms.

Drives Research & Innovation by identifying, prototyping, and scaling "next-gen" ideas within the travel domain, such as AI-driven automation for Travel Management Companies (TMCs) and personalized, real-time itinerary optimization.

Designs end-to-end AI systems, specifically focusing on the integration of Large Language Models (LLMs) for automated agency support, customer intent recognition, and conversational commerce.

Solves high-impact organizational challenges, such as optimizing Global Distribution System (GDS) workflows and migrating legacy automation logic into modern, GCP-based AI architectures.

Establishes strategic AI lifecycle policies, defining rigorous standards for MLOps to ensure high-fidelity model performance across the volatile data landscapes of the travel industry.

Promotes engineering excellence by utilizing best practices in Python and C++, ensuring research-grade prototypes are refactored into production-quality, low-latency systems.

Collaborates with cross-functional leadership, including architects and product managers, to align technical roadmaps with business goals like NDC adoption, total travel cost optimization, and operational efficiency.

Influences stakeholder decision-making, advocating for the adoption of disruptive technologies including Agentic AI within mission-critical, high-availability travel environments.

Mentors and develops junior data scientists and engineers, fostering a culture of rigorous experimentation, academic-level research, and high-performance engineering.

Qualifications and Education Requirements:

Minimum 5 years of related experience in Data Science, AI Engineering, or Operations Research.

Advanced Degree (PhD preferred) in Mathematics, Statistics, Computer Science, or Physics with a strong research background and a proven track record of innovation.

Proven experience in Agile Software Development, with a demonstrated ability to move complex models from the research phase to global production.

Expertise in advanced ML/AI solutioning, including Deep Learning, Reinforcement Learning, and Natural Language Processing (NLP).

High-performance programming skills, with mastery of Python, C++ for computationally intensive and latency-sensitive tasks.

Superior analytical skills, particularly in processing high-volume, real-time data from GDS, OTA, and airline sources.

Deep knowledge of the Modern AI Tech Stack, including GCP (Vertex AI, BigQuery), MLOps tools, and containerization (Docker, Kubernetes).

Proficiency in Generative AI frameworks and experience with RAG-based systems for workflow automation.

Self-motivated leadership, capable of driving complex, cross-functional projects to completion with minimal direction.

Desirable (Optional) Qualifications:

Experience in the Travel Industry, specifically within the Global Distribution System (GDS) or Online Travel Agency (OTA) space.

Domain knowledge in Airline Operations, including Departure Control Systems (DCS), network planning, or route profitability.

Advanced Optimization Modeling skills, including Linear Programming (LP), Mixed-Integer Programming (MIP), and experience with solvers like Gurobi or CPLEX.