Data Scientist & Engineer (f/m/d)

Your area of work:

The Chief Technology Officer (CTO) area is at the heart of the Information Technology division of Deutsche Börse Group. The CTO area develops and operates the group-wide IT infrastructure (network, data centers and cloud), the Group Data & Advanced Analytics and the Enterprise Architecture which significantly contribute to Deutsche Börse Group overall strategy. The CTO area drives digital transformation and leverages innovation while keeping production operations stable are the core pillars of the shared services.

We are looking for an experienced and analytically minded Data Scientist & Engineer to join our Group Data Services team. In this role, you will design, develop, and deploy data science solutions and data engineering pipelines that drive business value across Deutsche Börse Group. You will work with capital markets data - including price data, market data, and trading information from our exchanges such as Eurex, Xetra, and 360T - to build production-ready analytics, machine learning models, and scalable data products. You will collaborate closely with business stakeholders, data engineers, and product teams at the intersection of advanced analytics and financial markets infrastructure.

Your responsibilities:

• Design, develop, and deploy machine learning models and analytics solutions for capital markets use cases, including price analysis, market data quality, and trading analytics.
• Build and maintain scalable data pipelines using Databricks, Delta Lake, and related technologies to process high-volume financial market data.
• Analyze and model price data, order book data, and trading patterns from Eurex, Xetra, and 360T platforms.
• Implement MLOps practices using MLflow, including experiment tracking, model versioning, and automated deployment pipelines.
• Collaborate with business stakeholders to translate requirements into technical solutions.
• Support data quality and governance initiatives for market data products.
• Maintain comprehensive documentation for models and pipelines.
• Mentor junior team members and contribute to continuous improvement of team practices.

Your profile:

• Master's degree in Data Science, Computer Science, Statistics, Mathematics, Quantitative Finance, or comparable field; alternatively, Bachelor's with substantial relevant experience.
• 3-5 years of professional experience in data science, machine learning, or data engineering.
• Strong proficiency in Python with data science libraries (pandas, NumPy, PySpark, scikit-learn).
• Solid experience with SQL and analytical databases.
• Experience with Apache Spark and large-scale data processing.
• Strong skills in time-series analysis and statistical methods.
• Familiarity with version control (Git/GitHub) and CI/CD workflows.
• Excellent communication skills; fluency in English required.

Highly desirable:

• Hands-on experience with Databricks (notebooks, workflows, Delta Lake, Unity Catalog) or similar cloud-based data lake house platforms.
• Experience working with financial market data (price data, tick data, reference data).
• Understanding of capital markets concepts (trading venues, derivatives, equities, FX, market microstructure).
• Experience with MLflow and MLOps practices.
• German language skills.