Revenue Management Data Analyst
On-siteSanto Domingo, Nacional, Dominican Republic
Job Summary
Build and calibrate route-level demand forecasts using historical bookings, seasonality, and competitive schedules to recommend inventory controls and overbooking levels. Monitor fares and availability to run price tests and provide data-driven recommendations that balance yield and load factor. Track attach rates and conversion along the digital funnel to quantify revenue impact of bundles and propose actions to lift ARPP. Design and automate BI dashboards with KPIs such as RASM, PRASM, and forecast accuracy, delivering weekly performance readouts to leadership. Partner with Data/IT to improve pipelines for PNRs, O&D, and competitor fares, while supporting network changes with revenue scenarios and sensitivity analysis. Provide accurate revenue projections and post-implementation reviews for budget cycles and board updates.
Required Qualifications
- Advanced Excel
- SQL for querying large datasets
- proficiency in one analytics language (Python or R) for modeling and automation
- familiarity with BI tools (Power BI/Tableau/Looker)
- Knowledge of time‐series forecasting
- regression
- price elasticity
- optimization
- ability to validate models (back‐testing, error metrics)
- Understanding of airline RM concepts (fare classes, O&D control, nesting, spoilage, displacement)
- LCC pricing
- ancillary economics
- Ability to translate complex findings into clear recommendations for non‐technical stakeholders
- strong presentation skills
- Comfort working cross‐functionally with RM, Pricing, Digital/E‐commerce, Network Planning, and Finance in a fast‐paced environment
- Bachelors degree in Economics, Statistics, Data Analytics, Industrial Engineering, Finance, Computer Science, or related field
- 1–4 years of experience in revenue management, pricing, data science/analytics, or commercial finance—preferably in aviation or travel
Desired Qualifications
- Experience with airline datasets (PNR, O&D, MIDT/GDS, web analytics) and external sources (OAG/Diio/Sabre data)
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