Profile description

As a language data manager you work primarily with data: data cleaning, curation and management (e.g., as part of database or translation memory maintenance). You need to be familiar with data standards and repositories on the one hand, and planning and quality control on the other.

Typical tasks and responsibilities

Work with software and technologies tools

Transcription of audio files

Translation, interpreting, localisation, post-editing

In the following sections, you will find more details about what you need to know to effectively perform previously presented tasks. Please have in mind that maintaining a strong foundation of disciplinary, (inter)cultural and transversal skills is equally indispensable for success across all listed tasks and responsibilities.

Knowledge, skills and competences

Bachelor's
Management
Organizational
Curation
Repositories
Planning
Data literacy
Standards
Cleaning
Quality control

#1 Technical

Using and developing language technologies together with language engineers

This means that you know about different types of language technologies, such as CAT tools, machine translation engines and ChatGPT, and you know not only how to use them, but also have some knowledge of how they work; you also have some programming skills, e.g. in Python

#2 Organisational

Planning, managing and leading projects and teams

This means that you have some familiarity with entrepreneurship, you are able to manage different kinds of projects, plan their implementation, implement quality assurance procedures and ensure that teams work well together towards a common goal

#3 Data-oriented

Familiarity with language data and their collection, curation and (statistical) analysis

This means that you have some experience in collecting linguistic data (e.g. from corpora or from speakers, in an interview or an experiment), in curating them and storing them following a set of standards, and in analysing them (especially quantitatively)

#4 Research-oriented

Applying analytical and critical skills to approach problems and advance knowledge

This means that you are able to use linguistic data for doing research, framing questions through appropriate research design, thinking analytically and processing information critically

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