Principal Data Science Engineer

• 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