Data Science Engineer - 2025 Summer Intern

Sabre is seeking a talented Data Science Engineer to support the Sabre Labs Team. This person will report to Sabre Labs.

Sabre Labs is a travel and technology innovation lab exploring capabilities that will impact travel over the next decade. Through research, model development, deployment and communication, Sabre Labs strives to make the future real for our businesses and customers.

Airline industry is going through a drastic transformation in the area of retailing and distribution that requires very advance data analytics support to optimize revenue performance and customer experience. Recently introduced concepts of Offer/Order Management and Continuous Dynamic Pricing significantly expand opportunities for engaging with travelers through multiple touch points and creating personalized offers accounting for individual preferences and market context. These practices can substantially benefit from a combination of statistical and machine learning techniques leveraging huge volumes and variety of consumer and competitive data available in airline industry.

The Data Science Engineer applies expert level statistical analysis, data modeling, and predictive analysis on strategic and operational problems in airline industry. As an intern in the Sabre Labs Research team, you will leverage your statistical and business expertise to translate business questions into data analysis and models, define suitable KPIs, and graphically present results to a wide range of audiences including internal clients, sales, and development team. In addition, you will source data from multiple different data sources, write high-quality data manipulation scripts in Python, bash, goLang etc, develop and apply data mining and machine learning algorithms for advanced analysis and prediction.

Role And Responsibilities

• Work with subject matter experts to solve prediction/forecasting/optimization problem at hand.
• Assess the effectiveness and accuracy of data sources, data gathering and forecasting techniques.
• Develop custom data models and algorithms to apply to data sets and run proof of concept study.
• Leverage existing Statistical and Machine Learning tools to enhance in-house algorithms.
• Collaborate with software engineers to implement and test quality code for forecasting and data analytics models.
• Develop processes and tools to monitor and analyze data accuracy and models’ performance.
• Conduct logical analysis of moderate to very complex management problems and information systems and formulates mathematical models for resolution of real world problems
• Prepare written technical reports to management indicating solution or range of possible alternatives in rank of desirability and probability of success when there is no single resolution
  
  

Preferred Qualifications And Education

• MS/PhD in (or candidate for) Statistics, Operations Research, Computer Science, Mathematics, Machine Learning or related Quantitative disciplines.
• Proven ability to apply modeling and analytical skills to real-world problems.
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
• Solid programming skills with knowledge of Python. GO or C .
• Experience with deployment of machine learning and statistical models on a cloud and leveraging services in GCP.
• Extremely diverse/complex work is completed with minimal direction, diverse interactions, knowledge resource.
• Familiarity with airline, hospitality or retailing industries and decision support systems employed there.
• Experience developing customer choice, recommendation models
• Understanding of airline distribution, pricing, revenue management, NDC and Offer/Order Management concepts.