Data Scientist (all genders)

Data Scientist (all genders) Location Cologne Employment level App. w. professional exp. Function 11 Working time Full-time or Part-time Data Scientist (all genders) Location Cologne Employment level App. w. professional exp. Function 11 Working time Full-time or Part-time 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. 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 Behind the scenes Meet the Eurowings Digital Team! We are dreamers, doers, and enthusiasts...! Requirements What you'll need 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 Company About Eurowings Digital GmbH We want to unfold the world to our customers. Eurowings Digitals mission is to deliver the most convenient and affordable end2end travel experience by connecting the physical and digital world. While our customers enjoy their journey, we take charge of a carefree travel experience. Not only offering quality flights for affordable prices, but being a travel companion all along the way. From their first inspiration to their favorite travel memories. Therefore we launched a whole new company which puts their customer into their total focus. Together we are going to discover, develop and test new products along the whole customer journey, on- and offline. In agile and diverse teams we will revolutionize the way of travelling. www.eurowings-digital.de Join Us. apply .cls-2{fill:#fff;}

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 Behind the scenes Meet the Eurowings Digital Team! We are dreamers, doers, and enthusiasts...! Requirements What you'll need 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 Company About Eurowings Digital GmbH We want to unfold the world to our customers. Eurowings Digitals mission is to deliver the most convenient and affordable end2end travel experience by connecting the physical and digital world. While our customers enjoy their journey, we take charge of a carefree travel experience. Not only offering quality flights for affordable prices, but being a travel companion all along the way. From their first inspiration to their favorite travel memories. Therefore we launched a whole new company which puts their customer into their total focus. Together we are going to discover, develop and test new products along the whole customer journey, on- and offline. In agile and diverse teams we will revolutionize the way of travelling. www.eurowings-digital.de Join Us. apply .cls-2{fill:#fff;}