Principal Data Science Engineer 54 views

Job Description

DATA SCIENCE ENGINEER

Airline industry is going through a drastic transformation in the area of retailing and distribution that requires very advance data analytics support to optimize revenue performance and customer experience. Recently in-troduced concepts of Offer/Order Management and Continuous Dynamic Pricing significantly expand oppor-tunities for engaging with travelers through multiple touch points and creating personalized offers accounting for individual preferences and market context. These practices can substantially benefit from a combination of statistical and machine learning techniques leveraging huge volumes and variety of consumer and competitive data available in airline industry.
The Data Science Engineer applies expert level statistical analysis, data modeling, and predictive analysis on strategic and operational problems in airline industry. As a key member of the Sabre Operations Research team, you will leverage your statistical and business expertise to translate business questions into data analy-sis and models, define suitable KPIs, and graphically present results to a wide range of audiences including in-ternal and external clients, sales, and development team. In addition, you will source data from multiple dif-ferent data sources, write high-quality data manipulation scripts in R, Python, Perl, bash, etc, develop and ap-ply data mining and machine learning algorithms for advanced analysis and prediction. You will also utilize your strong communication skills to work with developers to support product development cycles and decision makers who need empirical data to promote sales and growth.Responsibilities

  • 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 cus-tomer needs and train customer for using and maintaining software.
  • Resolve customer complaints with software and respond to suggestions for improvements and en-hancements.

Job Requirements

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, sta-tistical tests and proper usage, etc.) and experience with applications.
  • Solid programming skills with knowledge of R, SQL, Python, PySpark or other data-extraction and analy-sis 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.

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

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