Senior Data Science Engineer

Architects, codes, and deploys complex software solutions or data intelligence pipelines 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 identifying new market opportunities in Media, integration of Large Language Models (LLMs) for various internal tools, 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, golang or 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 technologiesincluding Agentic AIwithin 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

Minimum 4 years of related experience in Data Science, AI Engineering, or Operations Research. Advanced Degree (Masters/PhD preferred) in Mathematics, Machine Learning, 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