Business Solutions Manager - Data Science & AI Projects (Revenue Management)

Overview

What you’ll do

• Lead data science, machine-learning and AI projects from ideation and model development through POC, deployment and productionization.
• Develop and enhance machine-learning models supporting dynamic pricing, forecasting, optimization and commercial decision-making.
• Play a key role in evolving our in-house ancillary dynamic pricing capability.
• Identify new opportunities to apply AI, machine learning and advanced analytics to real Revenue Management and commercial challenges.
• Build new analytical products while continuously improving existing models and solutions.
• Test, validate, calibrate and monitor models to ensure they continue to deliver measurable business value.
• Partner with Revenue Management, Digital, Technology & Innovation and Commercial teams to turn complex business problems into scalable technical solutions.
• Translate sophisticated analytical outputs into clear commercial insights that stakeholders can understand and act upon.
• Support adoption and change, ensuring new solutions become embedded in commercial decision-making.
• Extensive experience in leading the evaluation, implementation, and optimization of dynamic ancillary pricing capabilities to maximize ancillary revenue while enhancing customer value and conversion.
• Identify, evaluate, and implement Artificial Intelligence and Machine Learning use cases to improve operational efficiency, revenue generation, and customer experience.
• Promote the adoption of AI-driven insights and automation across commercial processes to support innovation and continuous improvement.

What we’re looking for

• A bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Information Technology or another relevant quantitative discipline.
• 5+ years’ experience across data science, machine learning, AI or advanced analytics.
• Strong hands-on experience building machine-learning models and taking them through the complete lifecycle into production.
• Strong Python and/or R capability and experience working with modern data science tools and platforms.
• Experience working with large, complex datasets and developing scalable analytical solutions.
• Experience with platforms such as Databricks and cloud environments including GCP, Azure or AWS.
• Strong project leadership and stakeholder management capability.
• The ability to explain complex technical concepts and model outputs in commercially meaningful terms.
• Knowledge of Revenue Management, pricing, forecasting or optimization would be highly valuable.
• Airline or travel industry experience would be strongly preferred, but we’re open to candidates who can demonstrate strong data science capability and the ability to apply it to complex commercial problems.