Sr Operations Research Engineer

Sabre is a technology company that powers the global travel industry. By leveraging next-generation technology, we create global technology solutions that take on the biggest opportunities and solve the most complex challenges in travel. 

Positioned at the center of the travel, we shape the future by offering innovative advancements that pave the way for a more connected and seamless ecosystem as we power mobile apps, online travel sites, airline and hotel reservation networks, travel agent terminals, and scores of other solutions.

Simply put, we connect people with moments that matter.

SABRE Professional Services and Consulting is looking for a talented Senior Operation Research Engineer


Role and Responsibilities

  • Key member of the Sabre AVPS Calibration team to leverage statistical and business expertise to translate business questions into data analysis and models, define industry aligned KPIs, and present results to a wide range of audiences including customers, teams, sales, and product development teams.
  • Source data from multiple different data sources, write high-quality data manipulation scripts in deployed programming language (currently R), develop and apply data mining and machine learning algorithms for advanced analysis and prediction / forecasting.
  • Strong communication skills to work with customers to implement solutions, calibrated parameters and support business owners and decision makers.
  • Execute Analytical Consulting services & designing end-to-end analytics solution for effective process flow that help an airline customer in selecting the right models, optimize practices and business processes
Primary responsibilities

  • Work directly with customers and internal stakeholders to implement decision support solutions
  • Periodically re-calibrate model parameters based on most recent available datasets
  • Engage directly with customers to deliver calibrated model parameters, validate forecasted results and achieve contracted KPIs in the set timelines
  • Collaborate internally with product development teams to conduct rigorous testing and validating new features to be released for production
  • Actively participate in evaluating model enhancements, introduce new features & processes aimed at increased customer adoption of the solutions
 
Qualifications and Education Requirements

  • Master’s degree (Preferably M.Sc. (Quantitative Subjects), M.B.A., M.E., M.Tech.) with minimum 4-5 years of relevant experience (or)
  • Bachelor’s degree holders (Preferably B.E., B.Tech) with minimum 5-6 years of relevant experience.
 
Must Have Skills:

  • Ability to understand complex business requirements and define KPIs to measure benefits and communicate complex quantitative analysis in a clear, precise, and actionable manner
  • Solid programming skills (expertise in any statistical tools like SQL / SAS / R / Python / other tools)
  • Experience with applying complex business logics to extract and cleanse large datasets from different data sources (xml, txt, xls, sql, etc)
  • Skills in Microsoft Tools (Preferably Excel and Power point)
  • Excellent communication skills, strong problem solving and analytical skills
  • Excellent Customer Management Skills and Ability to handle multiple projects
Nice To Have Skills:

  • Ability to read articles and develop new statistical, optimization and ML algorithms to fit the business needs and building predictive models for real-world business cases
  • Ability to quickly learn and program new tools for multi-dimensional data-driven decision support
  • Work with cross functional team and good presentation skills
  • Experience working in cloud environment
  • Experience working in visualization tools Google Looker
  • Familiarity with Airline & Travel Domain
We will give careful consideration to your application and review your details against the position criteria. You will receive separate notification as your application progresses.

Please note that only candidates who meet the minimum criteria for the role will proceed in the selection process.

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