Sr Data Scientist

Sabre Corporation•Dallas, TX

1d•Hybrid

About The Position

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. We are seeking a Data Science Engineer to join our global Operations Research team, where innovation knows no borders. This team applies advanced statistical analysis, data modeling, and predictive analytics to solve complex strategic and operational challenges in the airline industry. It helps airlines optimize revenue performance, advance retailing and distribution through Offer/Order Management and Continuous Dynamic Pricing, and elevate the traveler experience. With an inclusive culture and flexible work environment, we work together with boldness, curiosity and commitment so we can all win together. As a Data Science Engineer, you will translate complex business questions into robust statistical models, define critical KPIs, and communicate empirical results to internal and external decision makers. You will source data across diverse platforms, build high-quality data manipulation scripts, and apply machine learning algorithms to drive predictive insights and product development cycles. This role requires expert analytical capability, proactive collaboration with software development teams, and the drive to deliver measurable business outcomes.

Requirements

Advanced degree in Statistics, Operations Research, Computer Science, Mathematics, Machine Learning, or a related quantitative discipline.
Advanced programming skills in Python and modern C++, alongside proficiency in R, SQL, PySpark, Perl, bash, Java, or JavaScript.
Proven ability to apply advanced statistical concepts (regression, distributions, hypothesis testing) and machine learning techniques (clustering, decision trees, neural networks) to real-world problems.
Experience deploying statistical and machine learning models in cloud environments using services like Amazon SageMaker and Amazon Forecast.
Strong communication skills with demonstrated experience presenting graphical analytics to clients, sales, and software engineering teams.

Nice To Haves

Industry experience or domain knowledge in airline, hospitality, or retailing decision support systems.
Hands-on experience developing customer choice models, price elasticity estimations, and market potential estimations.
Practical understanding of airline distribution, pricing, revenue management, NDC, and Offer/Order Management concepts.

Responsibilities

Partner with airline subject matter experts to turn operational and consumer data into actionable predictions that optimize customer behavior and business performance.
Develop, test, and calibrate custom data models, forecasting techniques, and machine learning algorithms, performing proof-of-concept studies and proving value through benchmark demonstrations.
Sourced data from multiple data sources and write high-quality data manipulation scripts in R, Python, Perl, and bash.
Collaborate with software engineers to write, implement, and test production-quality C++ and Python code for forecasting and data analytics tools.
Establish monitoring processes and tools to continuously evaluate data accuracy, assess model performance, and resolve software improvements or customer complaints.