Description

Lead the development of predictive models and data-driven insights within the airline distribution and revenue management domain.

Responsibilities

• Partner with airline subject matter experts to identify opportunities for predicting customer behavior and operational performance.
• Develop custom data models, algorithms, and proof of concept studies to solve real-world problems.
• Collaborate with software engineers to implement and test production-quality code for forecasting and analytics models.
• Build processes and tools to monitor data accuracy and model performance.
• Calibrate software for specific customer needs, perform value-proving benchmarks, and provide technical training.

Required Skills

• 5+ years of experience applying modeling and analytical skills to real-world problems.
• Advanced Degree in Statistics, Operations Research, Computer Science, Mathematics, Machine Learning, or related quantitative disciplines.
• Proficiency in Python, R, SQL, or PySpark.
• Experience with programming languages such as Java, JavaScript, or C++.
• Knowledge of machine learning techniques including clustering, decision tree learning, and artificial neural networks.
• Strong grasp of advanced statistical techniques including regression, properties of distributions, and statistical testing.
• Experience deploying machine learning and statistical models on cloud services like Amazon SageMaker and Amazon Forecast.

Preferred Skills

• Domain knowledge of airline revenue management, demand forecasting, and price optimization models.
• Understanding of airline distribution, pricing, NDC, and Offer/Order Management concepts.

Key Skills

Education

Any Graduate