Data Scientist

Lufthansa Systems Poland is acclaimed and widely recognized provider of superior services and IT solutions for the aeronautical, logistic and financial industries. As a part of the Lufthansa Group we implement technological solutions and dedicated services.

• 3–5 years of commercial experience in a Data Scientist role or a similar position
• Strong analytical and problem-solving skills, with experience in Classical ML methods and discrete choice modeling
• Proficient in Python and machine learning libraries, with strong experience using Databricks for scalable analytics
• Experience with statistical methods, decision analytics, and revenue optimization
• Intermediate understanding of Large Language Models (LLMs) and Generative AI, with practical exposure to their application in enhancing analytics workflows or decision support systems
• A data scientist mindset with a strong sense of curiosity—actively seeks the meaning behind data patterns and continuously explores opportunities to align data science solutions with business processes and strategic goals
• A strategic mindset, capable of transforming complex datasets into actionable insights
• Strong communication skills, with the ability to translate complex data insights into clear, actionable recommendations for stakeholders across various business functions
• Ability to collaborate effectively in a fast-paced, cross-functional team environment
• Familiarity with SQL, database management and Microsoft Azure Environment is an advantage
• Good knowledge of English in speaking and writing (B2/C1)
• Working 2 days per week in Gdańsk office

Nice to have:

• Demonstrated expertise in passenger choice modeling development is a significant advantage
• Knowledge about Agile/Scrum methodologies.

• Develop and refine ML models in airline commercial processes to improve airline pricing, route planning, and revenue strategies
• Re-evaluate and challenge enhance passenger choice models to ensure optimal performance, robustness, and alignment with evolving market dynamics
• Contribute to PoC (Proof of Concept) and implementation of GenAI use cases across commercial and admin domains
• E2E deployment of Data Science project ETLs in Microsoft Azure environment
• Collaborate with business units and ensure close communication with Business end users by translating analytical findings into impactful commercial strategies
• Support machine learning and statistical model deployment, ensuring seamless integration into operational systems
• Conduct in-depth data analysis on airline revenue management, pricing strategies and customer segmentation
• Present actionable insights through compelling reports, data visualizations and presentations to leadership
• Preparing documentation of the particular steps and the final product.