Sr. Lead Data Scientist

Responsibilities

• Understanding of airline distribution, pricing, revenue management, NDC and Offer/Order Management concepts.

• Work with subject matter experts from airlines to identify opportunities for leveraging data to deliver in-sights 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 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 customer for using and maintaining software.
• Resolve customer complaints with software and respond to suggestions for improvements and enhancements.

• 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 improvements and enhancements.

Required Qualifications
• 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 ser-vices like Amazon SageMaker and Amazon Forecast.
• Knowledge of airline revenue management algorithms and experience of developing demand forecasting and price optimization models.