Job Descriptions:
- Data Analysis: Identify and analyze language data from various sources to uncover trends, patterns, and insights.
- Data Preparation: Build and curate linguistic datasets from multiple sources, ensuring data quality and relevance.
- Natural Language Processing (NLP): Develop and apply NLP models to process and analyz text data, such as sentiment analysis, entity recognition, and text classification.
- Data Visualization: Effectively visualize linguistic data and analysis results in a meaningful and informative way to facilitate decision-making.
- Reporting: Present findings and insights to business leaders, executives, and key stakeholders, and provide actionable recommendations based on linguistic analysis.
- Data Ethics: Uphold high standards of data ethics and ensure the responsible use of linguistic data, particularly in sensitive or culturally significant contexts.
- Tool Development: Collaborate with data engineers and scientists to design and implement tools and systems for linguistic data analysis, including language models and automation systems for content categorization and sentiment analysis.
- Localization and Cultural Adaptation: Assist in the localization of products and services by providing insights into linguistic nuances and cultural considerations.
Requirements:
- Experience: Minimum of 1 year of experience in a similar role, such as Data Linguist, NLP Specialist, or Computational Linguist.
- Linguistic Expertise: Strong understanding of linguistic theory, including syntax, semantics, and phonetics, with experience working with structured and unstructured language data.
- Technical Skills (optional):
– Experience with Python for linguistic data processing is a plus.
– Familiarity with NLP libraries and tools such as NLTK, SpaCy, or Gensim is a plus.
– Experience with related tools for deploying and managing NLP models is a plus.
– Experience with processing large-scale text data is a plus.
- Cloud Services: Experience with cloud platforms for deploying NLP models and handling language data.
- Communication Skills: Strong ability to communicate complex linguistic insights to non-experts, including business leaders and stakeholders.
- Cultural Sensitivity: Awareness and consideration of cultural contexts in linguistic analysis and data interpretation.