Data Scientist

Sabre is a technology company that powers the global travel industry. By leveraging next-generation technology, we create global technology solutions that take on the biggest opportunities and solve the most complex challenges in travel.

Positioned at the center of the travel, we shape the future by offering innovative advancements that pave the way for a more connected and seamless ecosystem as we power mobile apps, online travel sites, airline and hotel reservation networks, travel agent terminals, and scores of other solutions.

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 Scientist applies expert level statistical analysis, data modeling, and predictive analysis on strategic and operational problems in airline business. As a key member of the Sabre Operations 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 and external clients, sales, and development team. In addition, you will source data from multiple different data sources, write high-quality data manipulation scripts in R, Python, Perl, bash, etc, develop and apply data mining and machine learning algorithms for advanced analysis and prediction. You will also utilize your strong communication skills to work with developers to support product development cycles and decision makers who need empirical data to promote sales and growth.

Responsibilities

• Work with subject matter experts from airlines to identify opportunities for leveraging data to deliver insights and actionable prediction of customer behavior and operations performance.
• Assess the effectiveness and accuracy of new data sources, data gathering and forecasting techniques.
• Develop custom data models and algorithms to apply to data sets and run proof of concept studies.
• Design market sampling framework and incorporate obtained feedback into predictive and prescriptive methodologies.
• Collaborate with software engineers to implement and test production quality code for forecasting and data analytics models.
• Develop processes and tools to monitor and analyze data accuracy and models performance.

Required Qualifications

• Advanced Degree in Statistics, Operations Research, Computer Science, Mathematics, Machine Learning or related Quantitative disciplines.
• Ability to apply modeling and analytical skills to real-world problems demonstrated over 3-5 years of experience.
• 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 R, SQL, Python or other data-extraction and analysis tools and programming languages such as Java, JavaScript or C++.
• Experience working with and creating data architectures.
• Experience with deployment of machine learning and statistical models on a cloud service
• A drive to learn and master new technologies and techniques.

Desirable Qualifications

• Familiarity with airline, hospitality or retailing industries and decision support systems employed there.
• Experience developing customer choice models, price elasticity estimation and market potential estimation.
• Understanding of airline distribution, pricing, revenue management, NDC and Offer/Order Management concepts.

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