Degree in Mathematics, Computer Science, Economics, Industrial Engineering, Operations Research, or a related quantitative field 3-5+ years of experience in Revenue Management, Operations Research, Pricing, Analytics, or a related field Experience working with Revenue Management systems, forecasting models, pricing optimization, or decision-support tools Strong analytical, problem-solving, and stakeholder management skills Proficiency in SQL and Excel proficiency; BI tools experience is a plus Comfortable working with AI-assisted tools and eager to integrate them into daily workflows Ability to communicate complex analytical concepts effectively to both technical and business audiences

As an Operations Research Analyst (m/f/d) at Flix, you will directly influence the performance of our Revenue Management system by developing analytical solutions, validating system outputs, and supporting data-driven commercial decisions that improve network profitability. You will work closely with both tech and business teams in an Agile environment and will be part of the Revenue Management and Commercial Excellence Department, which is responsible for the revenue optimization of our full network. In particular, our department aims to define the best possible pricing strategy to maximize revenue based on current and historical demand patterns, competitor actions, and available supply. about the role design techniques to monitor, validate, and calibrate revenue management system outputs, including demand forecasts and optimized prices track business performance and develop data models and analytical tools to support optimal commercial decision-making collaborate closely with cross-functional teams and stakeholders to balance business value and complexity when defining the most suitable analytical approaches and methodologies monitor user actions (exempli gratia, pricing interventions and forecast adjustments) and assess their impact on business performance drive stakeholder adoption of revenue management processes and provide guidance on system usage and best practices leverage ai and machine learning tools to enhance analytical workflows and system performance monitoring