The Airline Solutions Data Science team at Amadeus designs, develops, and delivers data science, AI/ML, and algorithmic reasoning features at the core of Airline solutions products. Our solutions help airlines decide where and when to fly, how to allocate capacity, and how to price itineraries with the goal of maximizing network profitability.
Requirements
- Proficient in SQL and Python (5+ years).
- Strong foundation in statistical analysis and data modeling.
- Advanced analytical capabilities with experience handling complex datasets.
- Familiarity with orchestration tools, version control systems, and cloud architecture patterns.
- Proficiency in data visualization tools (e.g., Tableau, Power BI).
- Experience with the SAFe methodology.
Responsibilities
- Work to design, develop, and implement data-driven solutions in network planning, scheduling, or revenue management domains (including forecast, machine learning, AI, choice-modeling, optimization solutions, anomaly detection and more).
- Develop and maintain effective data models, algorithms, dashboards, and reports that provide actionable insights and support business strategies.
- Develop high-quality analytics applications, visualizations, statistics, and machine learning solutions that deliver value to our customers.
- Stay up to date with industry trends and best practices in business intelligence, forecasting, optimization, data visualization, revenue management, and airline network planning/scheduling to drive innovation and enhance the company's competitive advantage.
- Champion projects with cross-functional teams, including product managers, data engineers, customers, and stakeholders, to define business requirements and deliver data-driven solutions.
- Foster employee engagement in the development of a revenue management system while serving as a proactive change agent.
Other
- Minimum 5 years in analytical roles such as Data Scientist, Data Engineer, or Data Analyst.
- Preferred background in the travel industry, especially airline revenue management, scheduling, or network planning.
- Excellent communication and presentation skills; able to explain technical concepts to non-technical audiences.
- Strong problem-solving abilities and attention to detail.
- Demonstrated ability to work independently and collaboratively in fast-paced, deadline-driven environments.
