Responsibilities
- 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
Basic qualifications
- 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 (complex joins, window functions), and core data science libraries (Pandas, Scikit-learn, Matplotlib, XGBoost)
- Proficiency with Databricks or similar lakehouse/notebook platforms
- Familiarity with BI tools such as Power BI or Tableau
- Ability to select and justify modeling approaches based on data characteristics, business constraints, and interpretability requirements
- Understanding of model performance trade-offs (e.g., precision vs. recall) 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 (prompt engineering, evaluation, orchestration)
- At least 2–3 years of experience with MLOps practices and experiment tracking (e.g., MLflow)
- Experience working with at least one cloud platform (AWS, GCP, or Azure)
- Strong ability to communicate complex findings to non-technical stakeholders
- Strong analytical thinking with a commercial mindset — able to start from a blank canvas and create measurable value
- Curiosity to dig into unfamiliar business domains and ask "why" before jumping to modeling
- A bias toward pragmatic solutions — shipping an 80% model fast over perfecting one in isolation
- Comfort navigating ambiguity — translating vague business problems into structured analytical approaches
- Ownership of data quality — you question the data before trusting the output
- Ability to manage competing stakeholder priorities and align on what's worth solving
- Self-direction — you don't wait for a ticket to identify and pursue high-impact work
- Willingness to challenge assumptions, including your own
- Working knowledge of Kubernetes and Docker
- Experience with APIs (web services)
- Familiarity with stream processing frameworks (e.g., Kafka)
- Experience designing and analyzing A/B tests
- Knowledge of version control (Git)
- Experience building end to end AI applications
About the company
We are dreamers, doers, and enthusiasts!
Our mission is to enable our customers on leisure and/or business travel to enjoy a seamless travel booking experience from the tip of their fingers. Therefore, we are continuously working passionately on providing diverse and attractive offers on our online booking platforms Eurowings & Eurowings Holidays and mobile Apps to empower our customers with relevant information and smart digital services throughout their travel experience.
Tags & focus areas
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