Principal Data Scientist – Sabre Travel Technologies India Pvt Ltd
M.S in Computer Science, Furtwangen University, Germany
B.E. (Telecommunication), VTU University, Bangalore
John Kiran is a Principal Data Scientist with Sabre Airline Solutions (AS) team in Bangalore.
In Sabre, he is currently responsible for building and integrating machine learning algorithms across Sabre’s suit of products under AS portfolio.
He has more than 10 years of experience in data science and machine learning, mainly involved in implementing analytical methodologies/framework in Marketing/CRM environment.
Prior to Sabre, he has worked for prominent companies like VMware, HP, Dell and Genpact. One of his work titled “List price optimization – Using Customized Decision Trees” was published at MLDM (International Conference on Machine Learning and Data Mining 2016: 88-97).
John holds a master’s degree in Computer Science from Furtwangen University, Germany.
Keywork Areas
Machine Learning – Experience in implementing algorithms to gain insights into customer willingness to buy and price elasticity, resulting in unprecedented guidance using novel, patent pending techniques.
Quantitative analysis – Analyzing on consumer shopping behavior with respect to loyalty/ brand switching, new launches, consumer demographics and cross-purchasing
Training and workshops - Big Data and Analytics Trainer in data mining, Machine Learning and Big Data tools and technologies. Provide in depth training in a classroom environment for professionals and corporates.
Marketing Analytics – Involved in planning CRM activities and generating leads for the campaigns from Acquisition, Reactivation, At-Risk and Next Logical Purchase programs.
Topic Title: Dynamic Pricing Engine for Air Cargo
Abstract: Sabre® AirVision Cargo™ Revenue Manager (RM) is a decision-support product that transforms the process of managing an airline’s cargo capacity. In RM, bid prices are used to evaluate incoming cargo reservations to accept or reject bookings. Since the price calculation is not real-time, there is potential revenue leakage for airlines. In this presentation, we will discuss about price elasticity models that is used as a price guidance, in addition to fixed price, providing a lever to users on price range based on willingness to pay.