Description

Diverse/moderately complex work is completed under minimal supervision, internal and external interaction, may lead projects Employee can become proficient via a learned upper education curriculum such as a 4-year undergraduate degree as well as prior work experience in this or similar discipline Manager makes assignments by defining objectives, priorities and deadlines, and assists the employee with unusual situations which do not have clear objectives Employee plans and carries out successive steps and resolves problems and deviations in accordance with instructions, policies and accepted practices Supervisor reviews the work for technical adequacy and conformance with practice and policy 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 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 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 services like Amazon SageMaker and Amazon Forecast Knowledge of airline revenue management algorithms and experience of developing demand forecasting and price optimization models 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 concepts Core Skills Expert knowledge of statistics and probability theory Proficiency in at least one programming language such as Python, R, or SQL Advanced experience with data visualization tools such as Tableau or PowerBI Expert understanding of machine learning algorithms and models Advanced knowledge of data cleaning and preprocessing techniques Experience with data analysis and interpretation Strong communication and presentation skills

Role and Responsibilities

• Diverse/moderately complex work is completed under minimal supervision, internal and external interaction, may lead projects Employee can become proficient via a learned upper education curriculum such as a 4-year undergraduate degree as well as prior work experience in this or similar discipline Manager makes assignments by defining objectives, priorities and deadlines, and assists the employee with unusual situations which do not have clear objectives Employee plans and carries out successive steps and resolves problems and deviations in accordance with instructions, policies and accepted practices Supervisor reviews the work for technical adequacy and conformance with practice and policy 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 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 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 services like Amazon SageMaker and Amazon Forecast Knowledge of airline revenue management algorithms and experience of developing demand forecasting and price optimization models 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 concepts Core Skills Expert knowledge of statistics and probability theory Proficiency in at least one programming language such as Python, R, or SQL Advanced experience with data visualization tools such as Tableau or PowerBI Expert understanding of machine learning algorithms and models Advanced knowledge of data cleaning and preprocessing techniques Experience with data analysis and interpretation Strong communication and presentation skills