Data Scientist

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 improve sales, generate efficiencies and optimize existing processes.

What you\’ll do

• Create data products and deliver insights that support the goals and ambitions of Eurowings Digital and Eurowings Group
• Identify, evaluate, forecast, and provide recommendations on the optimization of our prices and products. Bring value in terms of personalized offerings, revenue and costs
• Work constantly on the accuracy, reliability and success rate of our data products. Monitor and optimize our data products / MVPs on a regular basis
• Work closely with Business 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

Our Tech Stack: Spark, Python, Scala, Azure Cloud, Databricks, MLflow, MS Analysis Service, MS Synapse, MS SQL

What you\’ll need

• University degree (preferably a Master\’s degree) in Economics, Computer Science or any STEM related field
• 2-4 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)
• Experience with ML techniques including decision trees, random forests, logistic regression, and time series forecasting
• Atleast 1 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

• Curiosity
• Innovation
• Problem-solving
• Communication
• Collaboration
• Self-motivation
• Adaptability
• Analytical thinking
• Data quality focus

Bonus Points

• 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
• Exposure to MS Fabric
• Knowledge of version control (Git)
• Familiarity with NLP

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