ABOUT EUROWINGS DIGITAL
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.
ABOUT THE JOB
As a Data Scientist (all genders) you are a key member of the Data Science team, responsible for creating analytical insights, developing data-driven products/solutions and building Machine learning/AI algorithms to increase efficiencies and productive in an airline Operations environment.
WHAT YOU'LL DO
- Create data products and deliver insights that support the goals and ambitions of Eurowings Digital and Eurowings Group Operations
- Identify, evaluate, forecast, and provide recommendations on the optimization of Ops processes including aircraft, airport and crew areas
- Work constantly on the accuracy, reliability and success rate of our Ops data products. Monitor and optimize our data products / MVPs on a regular basis
- Work closely with Business Analysts, Product Owners, Data Analysts, Data Engineers and other colleagues to deliver the best data products and processes end-to-end
- Keep track of the latest trends of the data science toolbox. Make our data products better by applying these new trends
WHAT YOU'LL NEED
- University degree (preferably a Master's degree) in Computer Science, Mathematics, Economics or any STEM related field
- 3-5 years of professional experience as a Data Scientist
- Solid understanding of Python, SQL (complex joins, window functions), and core data science libraries (e.g., Pandas, Scikit-learn, Matplotlib, XGBoost)
- Proficiency with Jupyter notebooks or notebooks on Databricks
- Can independently train, validate, and interpret regression, classification, and time series models
- Able to assess performance, understand trade-offs (e.g., precision vs recall), and perform basic hyperparameter tuning
- Comfortable with feature engineering, data cleaning, and managing data leakage and overfitting
- Familiarity with evaluation metrics for classification, regression, and time series (e.g., MAPE, RMSE, F1-score, R2 score)
- Experience with ML techniques including decision trees, random forests, logistic regression, and time series forecasting
- Preferrably 2-year Experience with MLOps practices
- Proficiency with SHAP and/or LIME for model explainability
- Experience working with at least one cloud platform (AWS, GCP, Azure)
- Familiarity with BI tools such as Power BI, Tableau, or similar
- Basic knowledge of CI/CD workflows and Docker (nice to have)
- Experience working with recommendation engines, dynamic pricing, forecasting, Customer data is a plus
- Strong ability to communicate insights to non-technical stakeholders
WHAT YOU'LL BRING
- Experience in managing multiple stakeholders at the same time
- Strong prioritization and self-management skills
- The ability to think strategically about business, product and technical challenges
- Outstanding communication skills where you give recommendations to cross-functional team members
- A proactive approach to your work
- Working knowledge of Kubernetes and Docker
- Experience with APIs (web services)
- Experience in Airline or Airport Operations environments
- Experience in building data products and AI products that support Operations / Logistics
- Familiarity with stream processing frameworks (e.g., Kafka)
- Experience designing and analyzing A/B tests
- Exposure to MS Fabric
- Knowledge of version control (Git)