The Principal Data Science Engineer applies advanced statistical and machine learning techniques to enhance airline operations and customer interactions through data-driven insights.
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.
Sabre is the global leader in innovative technology that leads the travel industry. We are always looking for bright and driven people who have a penchant for technology, are hackers at heart and want to hone their skills. If you are interested in challenging work, being part of a global team, and solving complex problems through technology, business intelligence and analytics, and Agile practices - then Sabre is right for you! It is our people who develop and deliver powerful solutions that meet the current and future needs for our airline, hotel, and travel agency 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 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.
- 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.
Required Qualifications
- 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
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 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.
#LI-Hybrid#LI-NG1
Top Skills
Bash
BigQuery
C++
Containers
Dataproc
GCP
Gcp Dataflow
Gcp Vertex Ai
Gke
Go
Java
Mlops
Perl
Python
R
Terraform
Sabre Corporation Bengaluru, Karnataka, IND Office
#7, Whitefield Main Road, Unit 1 & 2, Level 2, 3 & 4, Navigator Building, ITPB, , , Bengaluru, Karnataka , India, 560066
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