Taxonomy Engineer

Bedrijfsomschrijving

ASML is a Dutch high-tech company and one of the main suppliers of machines for the semiconductor industry, in particular steppers and scanners, which are used in chip making. Customers are often chip manufacturers. ASML's head office and business complex is in Veldhoven, where research and development and assembly take place in cleanrooms. The company also has sixty service points in fourteen countries to support the installation and delivery of machines and spare parts.

ASML was created from a joint venture between ASM International and Royal Philips. ASML delivers worldwide, but most of its customers are located in Asia. In 2011, 66% of sales were achieved in that region, 25% in the United States and just under 9% in Europe. The largest customer was responsible for a quarter of the total turnover. ASML's main supplier is Zeiss, a manufacturer of lenses and optical components. Zeiss's share in ASML's total purchasing costs is just under 30%. Due to the great mutual interests, both companies have entered into a strategic alliance; This can only be broken if one of the parties cancels three years in advance. ASML spends a lot of money on research and development.

Context

The 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 - (The below listed duties are not all inclusive. This position must also perform other duties as assigned.):

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

• Master's in Information Science, Computer Science, Computational Linguistics, or related field
• Experience with developing and deploying controlled vocabularies, taxonomies, ontologies, or knowledge graphs within cloud-based architectures
• 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

Other Information

Preferred start date: June 1st 2024

Assignment duration: 12 Months

FTE: 40 hours

Shift: Day shift

Working from home: Partially, 3 days in the office

Department: IT Solution Delivery

Preferred language: English

Motivation letter required: Yes

US Expert Control: No

2 rounds of interview - online via Teams.

Recruitment guidelines:

• All candidates that are proposed need to have a pre-employment check.
• This is a temporary position. A conversion to ASML Payroll is not applicable.