NLP Data Scientist

Role: NLP Data Scientist

Experience in natural language processing technologies and services with emphasis in one or more of the following:

• Data acquisition and NL modelling: harvesting NL data, rapid bootstrapping of domain-specific and multilingual NL models for named-entity, syntactic parsing, or text classification.
• NL systems: large-scale development and deployment, performance monitoring, tuning and optimization of NL models. Deploy machine learning models to cloud platforms ensuring scalability and reliability.
• NL methodology: grammar-based, data-driven and machine learning-based, hybrid approaches, deep learning and generative ai based approaches.
• NL technologies: spoken language understanding, language translation, natural language search, syntax-semantics.
• Interfaces using ontologies, discourse processing, language generation and summarization, interactive NL systems.
• In depth understanding of language processing technology, a strong software background and experience with processing large scale multilingual texts through effective use of computing resources.
• Perform exploratory data analysis and feature engineering to derive actionable insights.
• Collaborate and help build and maintain CI/CD pipelines for seamless integration of models into production.
• Monitor, tune, and optimize models for performance and cost-efficiency in cloud environments.
• Hands on experience with NLTK tool, tokenization, lemmatization
• Annotation of texts using NLP annotators such as inception
• Transforming a model from research to production and ability to fine-tune model performance in a production setting using adaptive/incremental machine learning techniques.
• Collaborate with engineering teams to create robust data pipelines and integrate NLP systems into broader applications.