The main responsibility of an Associate Linguistic Project Manager is to manage projects for Appen’s clients. The ALPM applies their knowledge of linguistic phenomena, technical skills and attention to detail to manage projects to quality expectations, timelines, and budget.
The ALPM applies their communication skills to manage stakeholder relationships and teams of language specialists around the world as well as in secure office locations in the UK and across Europe.
Duties & Responsibilities
Plan and manage projects to quality, time and budget to ensure effective project execution and delivery.
Onboard and train virtual teams of consultants to create, evaluate or annotate linguistic data in multiple languages using internet-based tools.
Onboard and train localised teams of consultants to create, evaluate or annotate linguistic data in multiple languages at secure office locations in UK and Europe.
Prepare guidelines, training materials and tools, aligned to client specifications.
Oversee the work of consultants, including task assignment, scheduling and monitoring.
Ensure close and regular communication with all internal project stakeholders.
Document and manage language resources arising from projects.
Experience in a language-related field, such as linguistics, computational linguistics, translation and localization, or equivalent.
Linguistic proficiency in one of the following : Hindi, Tamil or Mandarin.
Good technical and data management skills.
Good problem-solving and analytical skills.
Demonstrated ability to work effectively in an environment characterised by constant change, and a fast, deadline-driven culture.
Willingness and ability to travel both within UK and Europe for short periods of time : current UK / EU passport required
Willingness to undergo background checks at various levels for clearance to access secure data and locations
Project management experience, preferably in a language, linguistics, or software-related field.
Degree in linguistics, computational linguistics or language-related studies, or equivalent experience.
Understanding of linguistic concepts and terminology.
Some experience with regular expressions, bash scripting, python or programming skills.
Native or near-native proficiency in at least one language other than English.
Exposure to a range of Natural Language Processing technologies.
Experience using open-source transcription applications.
Some experience in workplace training or educational background.