Team Lead Data Science Engineer

Lead Data Science Engineer

Powering the agentic revolution in travel. Sabre is an AI-native technology leader, backed by one of the world's largest travel data clouds. Built on an open, modular, cloud-native architecture, Sabre serves as the backbone for both established leaders and bold, new disruptors, guiding them to the next age of travel retailing through intelligent, connected, and personalized experiences. With AI at its core and operating at unparalleled scale, Sabre transforms insights into innovation, empowering airlines, hoteliers, agencies and other partners to retail, distribute and fulfill travel worldwide.

Sabre is seeking a talented Lead 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 Sabre's travel marketplace. We are dedicated to solving complex challenges across the global travel domain, including Airline Pricing, Agency Automation, Network Planning, Airline Operations, and Departure Control Systems (DCS). 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, we're passionate about building software that solves problems. In this role, you will lead the planning, design, and development of software systems and applications, working under general direction to translate complex research into production-ready cloud tools.

Role and Responsibilities

• Leads the development and deployment of complex software solutions that integrate advanced mathematical algorithms and machine learning models into Sabre's core platforms (Retailing, Network Planning, Agency Automation, and DCS).
• Acts as a Technical Liaison, coordinating diverse interactions between research, architecture, and product management teams to ensure alignment with overall objectives.
• Executes Research & Innovation by prototyping and scaling "next-gen" ideas, such as AI-driven automation for Travel Management Companies (TMCs) and real-time itinerary optimization.
• Drives technical execution of end-to-end AI systems, focusing on the integration of Large Language Models (LLMs) for automated agency support and conversational commerce.
• Resolves technical conflicts and coordinates work with others to overcome hurdles in migrating legacy automation logic into modern, GCP-based AI architectures.
• Refines AI lifecycle standards, implementing MLOps best practices to ensure high-fidelity model performance across diverse and volatile travel data sets.
• Ensures engineering excellence by utilizing Python and C++ to refactor research-grade prototypes into production-quality, low-latency systems.
• Exercises initiative in interpreting policy and technical standards, keeping leadership informed of project progress, controversial matters, or far-reaching technical implications.
• Provides technical mentorship and guidance to team members, fostering a culture of rigorous experimentation and high-performance engineering.

Qualifications and Education Requirements

• Minimum 6 years of related experience in Data Science, AI Engineering, or Operations Research.
• Advanced Degree (MS required, PhD preferred) in Mathematics, Statistics, Computer Science, or Physics with a strong research background.
• Experience in fast-paced Software Development in an Agile environment, with a proven track record of moving models from the research phase to production.
• Expertise in ML/AI solutioning, including Deep Learning, Reinforcement Learning, and Natural Language Processing (NLP).
• Solid programming skills in Python and C++ for computationally intensive and latency-sensitive tasks.
• Strong analytical skills, with experience processing high-volume, real-time data from GDS, OTA, or airline sources.
• Knowledge of the Modern AI Tech Stack, including GCP (Vertex AI, BigQuery ML), MLOps tools, and containerization (Docker, Kubernetes).
• Familiarity with Generative AI frameworks, such as Gemini and experience with RAG-based systems.
• Excellent communication skills in English, with the ability to coordinate work across diverse teams and present technical updates to supervisors.

Desirable (Optional) Qualifications:

• Experience in the Travel Industry, specifically within GDS, OTA, or Airline domains.
• Domain knowledge in Airline Operations, Departure Control Systems (DCS), or Network Planning.
• Optimization Modeling skills, including Linear Programming (LP), Mixed-Integer Programming (MIP), and experience with solvers like Gurobi or CPLEX.