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Cargo Inventory Analytics Specialist

Qatar Airways
Doha, QAT
Full Time
Mid
Onsite
2 weeks ago
Data AnalysisStatistical ModelingPythonRMachine LearningOptimization Models
Free

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General Information

  • Ref #: 233510
  • Location: Qatar Doha
  • Job family: Cargo & Airport Operations
  • Closing Date: 2026 07 11

Description

  • The air cargo industry is in an accelerated phase of change and transformation.
  • Qatar Airways Cargo is leading this change as the world's largest global air cargo carrier.
  • We are looking for talents – the bold, the imaginative and the change maker.

About The Role

  • Responsible for supporting in developing and setting a selection of inventory controls across the QR network (Passenger and Freighter flights).
  • Support Cargo Inventory Analytics Manager in setting the optimal mix between allotment and free sale capacity, overbooking levels and commercial controls.

Responsibilities

  • Analyze and implement optimal levels of allocation capacity across the QR cargo network on a seasonal basis.
  • Analyze and set commercial entry parameters for structural demand such as RFQ's or allocations.
  • Analyze and set commercial entry parameters for ad hoc demand.
  • Develop and suggest initiatives to improve the setting of commercial controls by conducting data analysis and running optimization models.
  • Communicate new or updated inventory control initiatives to regional stakeholders and among the wider RM team.
  • Propose improvements to inventory control setting in team meetings or to the line manager.
  • Define seasonal impact of payload limitations for any impacted route(s) across the network.

About You

  • Bachelor’s degree with minimum 4 years of job related experience.
  • Experience of working with data modelling tools and running large data analysis exercises.
  • Strong grasp of statistical concepts and applications such as regression, hypothesis testing, probability distributions, treatment effects, etc.
  • Ability to communicate complex concepts intuitively to non technical audience.
  • Good knowledge of Machine Learning algorithms, statistical models, optimization models, simulation, and model evaluation techniques strongly preferred.
  • Previous experience of having worked in the Air Cargo domain is preferred.
  • Ability to work with data modelling tools (such as R, and Python).

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