Detailansicht des Stellenangebots

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

Ihr Profil:

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