Join our team of data science and machine learning experts to shape next-generation pricing strategies! We combine cutting-edge techniques - like price elasticity modeling, bid price strategies, and advanced ML - to optimize pricing decisions for millions of customers. Our work directly drives efficient revenue management processes and enhances the user experience.
We’re looking for a Senior Data Scientist – Operations Research (m/f/d) with deep revenue management expertise and a solid background in mathematical optimization. Ideal candidates have hands-on experience in dynamic pricing, bid price optimization, and have worked in (or closely with) the airline or car rental industry.

YOUR SKILLS MATTER

• Industry Experience: You have 5+ years experience in data science and operations research roles, ideally in car rental, airlines, or similar travel/hospitality sectors
• Revenue Management Expertise: You have proven track record implementing or optimizing revenue management systems and pricing strategies
• Optimization & Solvers: You have a strong background in mathematical optimization (linear, nonlinear, integer programming), solvers, and algorithm design (dynamic/stochastic programming)
• Machine Learning & Forecasting: You are proficient in demand forecasting, time series modeling, and modern ML techniques (especially regression)
• Programming Skills: You have expertise in Python for data analysis, modeling, and production deployment. Familiarity with version control systems (e.g., Git)
• Analytical Mindset: You show ability to translate complex business problems into actionable analytical tasks and clearly communicate findings to various audiences

ADDITIONAL PREFERRED QUALIFICATIONS

• Pricing & Bid Price Optimization Practical experience designing or implementing bid price models in large-scale revenue management systems
• Education Master’s degree (or higher) in Operations Research, Applied Mathematics, Statistics, or a related quantitative field

• Revenue Management & Price Optimization: You design, develop, and deploy advanced revenue management systems focusing on dynamic pricing and bid price optimization strategies
• Operations Research Modeling: You formulate and solve complex optimization problems (linear, nonlinear, dynamic, stochastic) to maximize revenue and support key decision-making processes
• Demand Forecasting & Customer Willingness-to-Pay: You create and refine forecasting models using time series and machine learning methods to capture customer demand and willingness-to-pay
• Algorithm & Tool Development: You build and maintain robust algorithms that integrate seamlessly with production systems, ensuring efficiency and scalability
• Cross-Functional Collaboration: You work closely with product managers, data engineers, and software developers to deploy end-to-end solutions and continuously improve analytical models
• Thought Leadership: You stay current on the latest research in revenue management, operations research, and machine learning; and you provide mentorship and guidance to junior team members