Data Scientist

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.