Data Scientist (Revenue Management)

Location: Open to contractors based in Poland

Rate: 89–119 per hour (B2B)

Company

Flix develops and operates a transportation network with automated pricing and revenue management systems.

What you will do

• Further develop demand forecasting and price elasticity models driving automatic pricing across the Flix network.
• Research and test improved price-elasticity approaches from initial hypothesis through validated, production-ready model.
• Advise product and business counterparts on forecast and pricing-model problems, solution ideas, and feasibility.
• Contribute to technical brainstorming, modelling discussions, and implementation of reliable production solutions.
• Monitor and analyse pricing-product behaviour, respond to support cases, and improve system reliability and observability.

Requirements

• Strong academic background in mathematics, physics, statistics, operations research, quantitative economics, or a related field, with solid grounding in statistics and data analysis.
• Alternatively, proven hands-on expertise in price elasticity or demand modelling, such as experience in pricing or revenue management in transport, travel, hospitality, or retail.
• Critical thinking and attention to detail, including questioning assumptions, checking results, and deriving solutions in a complex environment.
• Programming experience, preferably Python; strong experience in another language is acceptable.
• Good SQL skills and basic knowledge of machine learning.
• Strong communication skills for explaining approaches and results to technical and non-technical colleagues.
• Ability to implement models independently and ensure they run reliably.
• Ability to collaborate with stakeholders and build resilient working relationships in a remote setup.

Culture & Benefits

• Freelance/service-agreement cooperation as a B2B contractor, not an employment contract.
• Operate as an independent contractor, deliver agreed services, and submit invoices.
• Collaboration with product, business, and technical stakeholders on production data-science systems.