Inserat online seit: Veröffentlicht vor 20 Std.
Aufgaben der Stelle
As a Data Scientist (all genders) you are a key member of the Data Science team, responsible for creating developing data-driven products/solutions and building Machine learning/AI algorithms to improve sales, generate efficiencies and optimize existing processes across Eurowings commercial disciplines.
Tasks What You'll Do
- Design, develop, and deploy machine learning and AI solutions that solve commercial problems across pricing, demand, and revenue optimization
- Own model quality end-to-end — monitor performance, improve accuracy, ensure explainability, and quantify business impact throughout the model lifecycle
- Collaborate with Business Analysts, Data Engineers, Revenue Management, and Subject Matter Experts to deliver production-grade data products
- Identify opportunities where emerging techniques (GenAI, advanced forecasting, optimization) can create measurable business value — and build them
Our Tech Stack
PySpark, Python, Databricks, Azure Cloud, MLflow
Requirements
- University degree (preferably Master's) in Economics, Computer Science, or a STEM-related field
- 4–5 years of professional experience as a Data Scientist or ML Engineer
- Solid understanding of Python, SQL and core data science libraries
- Familiarity with BI tools
- Proficiency with Databricks or similar lakehouse/notebook platforms
- Ability to select and justify modeling approaches based on data characteristics, business constraints and interpretability requirements
- Understanding of model performance trade-offs and hyperparameter tuning
- Experience with feature engineering, data cleaning and managing data leakage and overfitting
- Experience with constrained optimization models
- Experience building RAG pipelines or integrating LLMs into production workflows
- At least 2–3 years of experience with MLOps practices and experiment tracking
- Experience working with at least one cloud platform
What You'll Bring
- Curiosity to dig into unfamiliar business domains and ask “why”
- A bias toward pragmatic solutions
- Comfort navigating ambiguity
- Ownership of data quality
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Standort
Eurowings Digital, Cologne
