[Hiring] Data Science Engineer @Sabre Corporation

Role Description

The Data Science Engineer applies expert level statistical analysis, data modeling, and predictive analysis on strategic and operational problems in the airline industry. 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.
• Graphically present results to a wide range of audiences including internal and external clients, sales, and development teams.
• 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.
• Utilize 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 predictions 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.
• Leverage existing Statistical and Machine Learning tools to enhance in-house algorithms.
• 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.
• Demonstrate software to customers and perform value proving benchmarks.
• Calibrate software for customer needs and train customers for using and maintaining software.
• Resolve customer complaints with software and respond to suggestions for improvements and enhancements.

Qualifications

• Knowledge of airline revenue management algorithms and experience of developing demand forecasting and price optimization models.
• Advanced Degree in 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 R, SQL, Python, PySpark or other data-extraction and analysis tools and programming languages such as Java, JavaScript or C++.
• Experience with deployment of machine learning and statistical models on a cloud and leveraging services like Amazon SageMaker and Amazon Forecast.

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.