Principal Data Science Engineer

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.

Simply put, we connect people with moments that matter.

• 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. 
• Leverage existing Statistical and Machine Learning tools to enhance in-house algorithms. 
• Collaborate with software engineers to implement and test production quality code for AI/ML 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 customer for using and maintaining software. 
• Resolve customer complaints with software and respond to suggestions for enhancements. 

• MS/PhD Degree in Statistics, Operations Research, Computer Science, Mathematics, or Machine Learning. 
• Proven ability to apply modeling and analytical skills to real-world problems. 
• Knowledge of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and statistical concepts (regression, properties of distributions, statistical tests, etc.). 
• Solid programming skills Python + 1-2 languages out of Java, C++, GoLang
• Experience with deployment of machine learning and statistical models on a cloud that includes a combination of following -
• MLOps within the enterprise CI/CD process for ML models (GCP Specific experience is very desirable, although Azure or AWS experience is also relevant) 
  • Experience deploying ML APIs in production environments in GCP using GKE
  • Experience in using GCP Vertex AI for ML and BigQuery
  • Knowledge in Terraform and Containers technologies
  • Experience writing data processing jobs using GCP Dataflow and Dataproc
  • Experience setting up ML model monitoring and autoscaling for ML prediction jobs
  • Understanding of machine learning concepts to scale ML across different services by leveraging Feature Store, Artifacts Registry and Analytics Hub

• 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 concept

We will give careful consideration to your application and review your details against the position criteria. You will receive separate notification as your application progresses.

Please note that only candidates who meet the minimum criteria for the role will proceed in the selection process.