Remote Opportunity: Lead Data Scientist with Airlines or Hospitality experience

Hello All, Hope you are doing great Please go through the job description and let me know your interest. Role: Lead Data Scientist with Airlines or Hospitality experience Location: Remote Duration: 12 months Top Skills: 4 to 6 yrs as Lead Google Cloud (GCP) that is the preference but other cloud experience will work. Programming- Python and C Data: PySpark Experience with Rally and JIRA is... good. Airlines experience is a must or at least Hospitality experience. Revenue Management experience is a plus as well. Job Description: Description Client is a leading technology provider to the global travel and tourism industry. Headquartered in Southlake, Texas, USA. we serve customers in more than 160 countries around the world. At Sabre, we make travel happen. Positioned at the center of the business of travel, our platform connects people with experiences that matter in their lives. Today, we're creating a new marketplace for personalized travel. It is our people who develop and deliver powerful solutions that meet the current and future needs for our airline, hotel, and travel agency customers. Join our journey! 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 introduced concepts of Offer/Order Management and Continuous Dynamic Pricing significantly expand opportunities 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 analysis and models, define suitable KPIs, and graphically present results to a wide range of audiences including internal and external clients, sales, and development team. In addition, you will source data from multiple different 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 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 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. Carrier Ladder Team Lead MS 6 years Diverse/complex work is completed under general direction, diverse interactions; liaison. Manager sets the overall objectives and resources available. Employee carries out the assignment, resolves most of the conflicts, coordinates work with others and interprets policy on own initiative. Employee keeps the supervisor informed of progress, potentially controversial matters, or far-reaching implications.

Thanks & Regards,

Satnam Singh

Direct: 201 623 3660

Email : [email protected]

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