Social network you want to login/join with:
Client:
ZEISS Group
Location:
Job Category:
-
EU work permit required:
Yes
Job Reference:
462b4a0f86cb
Job Views:
1
Posted:
05.05.2025
Expiry Date:
19.06.2025
Job Description:
Your Role
You will play a crucial role in shaping the future of Data & Analytics and actively contribute to the success of the digital transformation at ZEISS. Within the Enterprise Data Management Team of our rapidly growing Data & Analytics organisation, you will help our business units to design, build, and maintain knowledge-based systems, driven by the vision to enable everyone to effectively find, learn, share, & innovate throughout the enterprise.
You will:
- Integrate information into knowledge-graph based systems and engage in data & knowledge / ontology modelling, knowledge graph construction, and validation.
- Develop and apply algorithms based on graph queries / analytics (e.g., SPARQL), graph reasoning (e.g., RDFS+, OWL), AI/ML (e.g., NLP, graph embeddings) to enable various analytics use cases leveraging knowledge graphs.
- Work in a team with data scientists, data & software engineers & product owners to create scalable, reusable, and performant data-oriented applications, including chatbots, recommender systems, search, and other knowledge-based systems.
- Convey technically difficult concepts in a clear and understandable way, translate business needs to technical specifications, and provide guidance for knowledge graph & ontology development to other teams.
- Evaluate the latest methods and technologies and support the design of our data & analytics platforms and governance infrastructures. Continuously improve quality and performance while owning applications from idea to operations.
Your profile
- An excellent university degree (MSc/PhD) in information technology, computer science, natural sciences, or similar training.
- At least 3 years of working experience in data integration, building (semantic) knowledge graphs, querying (graph) data using standard query languages (SQL, SPARQL).
- Familiarity with machine actionable languages (e.g., RDF), linked data principles and standards, & OWL-based ontology modelling in commonly used tools.
- Solid understanding of at least one of Graph Analytics, Machine Learning / Deep Learning, Natural Language Processing.
- An independent (“can-do”), solution-oriented and team-oriented way of working, not afraid to take on responsibility.
- Strong desire to learn & upskill at the intersection of data, science & industry.
- Experience with the following is welcome and considered as a plus: Cloud technologies like Microsoft Azure (e.g., Synapse, Databricks, Azure DevOps), CI/CD using e.g., git, docker, Agile software-development using Scrum / Kanban.