Responsibilities:

• Collaborate with airline experts to leverage data for actionable predictions of customer behavior and operational performance.
• Evaluate new data sources and forecasting techniques for effectiveness and accuracy.
• Develop custom data models and algorithms and run proof-of-concept studies.
• Use statistical and machine learning tools to enhance existing in-house algorithms.
• Work with software engineers to implement and test production-quality code for forecasting and data analytics models.
• Create tools to monitor and analyze data accuracy and model performance.
• Demonstrate software to customers, perform benchmarks, calibrate software for customer needs, and provide training.
• Resolve software complaints and respond to suggestions for improvements.

Required Qualifications:

• Advanced degree in Statistics, Operations Research, Computer Science, Mathematics, Machine Learning, or related fields.
• Proven ability to apply modeling and analytical skills to real-world problems.
• Knowledge of machine learning techniques and their practical applications.
• Expertise in advanced statistical techniques and their applications.
• Strong programming skills in R, SQL, Python, PySpark, and familiarity with other programming languages like Java, JavaScript, or C++.
• Experience deploying machine learning and statistical models on cloud platforms, utilizing services like Amazon SageMaker and Amazon Forecast.
• Knowledge of airline revenue management algorithms and experience developing demand forecasting and price optimization models.

Desirable Qualifications:

• Familiarity with the airline, hospitality, or retail industries.
• 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.