Senior ML Engineer / Data Scientist Customer Data

About Deichmann

As a privately-owned family business, Deichmann is more than just a retail network spanning approximately 4,700 locations in 34 countries, boasting over 8.7 billion Euros in annual sales and operating one of Europe's most successful online shoe shops. Deichmann is a pioneer, supporter, and employer for over 49,000 dedicated employees worldwide. As a sustainably expanding company, we have been able to offer secure jobs to our employees for several decades.

As a Senior ML Engineer / Data Scientist Customer Data, you will strengthen our Data & Analytics Unit and actively contribute to building data-driven products that directly influence business decisions. In close collaboration with our specialist departments, we create added value on a modern cloud platform – whether in the context of Omnichannel, Marketing, CRM, Pricing, Purchasing, or Logistics. We rely on Python, SQL, Databricks, MLflow, and Airflow – always with the goal of improving our business and satisfying our customers.

Your Responsibilities

• You develop and operate customer-centric data and feature models as the foundation for ML, CRM, and Analytics applications within the Deichmann Group.
• You process structured, semi-structured, and unstructured data, then design scalable data structures such as event models, customer snapshots, and feature layers – implemented collaboratively with Data Engineers and platform teams.
• You develop robust ML features for customer-centric models (CLV, Churn, Segmentation, Next-Best-Action) – with a focus on time consistency and productive inference.
• You ensure consistency, versioning, and Data Governance across all customer-related features and define standards for their further development.
• You evaluate new use cases, translate business requirements into feature concepts, and guide teams from Proof of Concept (PoC) to productive operation.

Your Profile

• You hold a completed MINT degree; a PhD is a plus.
• You bring at least 5 years of experience in Data Engineering, ML Engineering, or Customer Analytics – with at least 3 years in a productive ML environment.
• You possess excellent knowledge of SQL and Python, as well as a deep understanding of Feature Engineering and ML Pipelines.
• You are familiar with the typical pitfalls of productive ML systems: Feature Stability, Data Drift, Training/Serving Skew, and MLOps.
• You are proficient in versioning, testing, architectural patterns, and CI/CD, and have experience building scalable data products.
• You demonstrate strong analytical skills and a pragmatic, hands-on mentality.
• Very good German language skills are required; good English language skills are essential.

Benefits

• 30 days holiday
• Flexible working hours
• Daily mobile working (hybrid)
• Discounted DeutschlandTicket (public transport)
• Company pension scheme
• Kindergarten places
• Bistro
• Staff discount
• Support fund
• Seminars & further training
• Company health management
• Company events

Key skills/competency

• ML Engineering
• Data Science
• Customer Data Models
• SQL
• Python
• Feature Engineering
• ML Pipelines
• MLOps
• Data Governance
• Cloud Platforms