Job description:
Knowledge Management (KM) Capability sits at the intersection of enterprise platform service design, semantic data engineering, and taxonomy governance for the organization. The team operates in a multi-faceted role, which includes performing complex data analysis to improve knowledge representation and consumption of unstructured data in systems, develop data transformation pipelines that join multiple data sets in the ASML knowledge graph, and collaborating across the organization to help define the customer experience for knowledge discovery and access on the Progress Semaphore platform. Members of the KM team own the end-to-end development of knowledge graph features for ASML recommendation engines, data, and content domains, using both industry standards and proprietary technical tools.
Responsibilities:
As a Semantic/Knowledge Engineer on the KM team, you will contribute to projects focusing on the design, creation, and deployment of knowledge models that translate business needs and domain expertise into machine actionable platform level services.
Primary responsibilities will include:
- Co-Designing the Enterprise Taxonomy in partnership with Learning & Knowledge Management department and several IT Teams
- Leading all aspects of Design, Publish & Maintenance of Enterprise Taxonomy Artifacts, Best Practices, Guiding Principles, Methodologies, and Standards
- Oversight of ASML’s metadata assets, primarily taxonomy, ontology, and content data
- Supporting current semantic structures, such as multiple ontologies and knowledge graphs, though semantic modeling techniques
- Modeling metadata and ontology schema to develop new semantic representations for supporting recommendation functionality
- Working with internal teams to guide the development and usage of knowledge structures that enable actionable information to data consumers and applications
- Supporting current and establishing new ETL processing rules and data workflows to support and grow current infrastructure
- Collaborating with Product, Software Development and Content teams to support current and future API integrations for semantically enabled applications, including recommendation functionality.
- Working with domain and business experts to translate requirements into knowledge models that support machine decision making
Education and Experience:
- Knowledge/experience with some knowledge technologies like knowledge graphs, graph databases, text mining, NLP, ontology engineering, machine learning
- Ability to use graph technology such as RDF triple stores to support enterprise level data solutions
- Knowledge of designing and validating metadata models and frameworks for varied data and content types Knowledge of / experience with Progress Semaphore platform
- Expertise in text analytics and data analysis specifically related to unstructured data
- Experience working with content and domain experts to gather requirements Knowledge in agile process frameworks like Kanban and Scrum is an advantage
Required skills:
- Proficiency in SQL, SPARQL, RDFS, SKOS or additional query languages
- Demonstrates ability to construct and design ontologies that support knowledge graph deployment
- Competence in using Python libraries specifically focused on dealing with unstructured text data and knowledge mining
- Ability and willingness to learn new technologies and tools
- Capacity to work with Semantic Web Technologies
- Basic Natural Language Processing (NLP) skills
- Proficient knowledge of AWS or cloud-based environments
- Knowledge in data visualization tools/techniques
Contact
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