Female Sales Executive

US-Bangla Airlines | Executive – Business Intelligence | Deadline: January 15, 2026

A reputed airline is seeking a highly analytical and tech-driven professional for the position of Executive – Business Intelligence. The ideal candidate will support data-driven decision-making across airline operations, revenue management, finance, and customer experience.

Job Summary

Position: Executive – Business Intelligence
Employment Status: Full-Time
Job Location: Dhaka
Age Limit: At most 28 years
Experience: At most 1 year (Freshers encouraged to apply)
Salary: Tk. 30,000 – 35,000 (Monthly)
Workplace: Work at Office

Educational Requirements

  • Bachelor of Science (BSc)
  • Master of Science (MSc)
  • Preferred disciplines:
    • Computer Science & Engineering
    • Applied Statistics
    • Data Science
    • or any related field

Experience Requirements

  • At most 1 year
  • Experience in the airline industry (PSS, GDS, DCS, Loyalty) is an advantage
  • Fresh graduates are welcome to apply

Additional Requirements

  • Age: At most 28 years
  • Strong command over:
    • Power BI, Tableau, Qlik, or other BI tools
    • SQL and data warehouse technologies
  • Excellent analytical, problem-solving, and presentation skills
  • Ability to interpret complex data into actionable business insights
  • Ability to work with cross-functional teams

Key Responsibilities

  • Manage and maintain the airline’s data warehouse and BI platforms, ensuring data accuracy across PSS, Loyalty, Finance, and other systems.
  • Develop automated dashboards for key airline KPIs:
    • Passenger Load Factor
    • Yield
    • Revenue
    • On-Time Performance (OTP)
    • Customer Satisfaction
  • Support Revenue Management & Sales teams through advanced analytics on:
    • Route profitability
    • Demand forecasting
    • Pricing strategies
    • Ancillary revenue opportunities
  • Analyze booking trends and loyalty program data to build predictive models for churn prevention and targeted marketing.
  • Deploy machine learning models for:
    • Dynamic pricing
    • No-show prediction
    • Automation of manual reports
  • Work closely with senior leadership to translate data insights into strategic business recommendations.

Source: Facebook

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