NLP Data Scientist

Role Overview: You will play a pivotal role in enhancing the natural language processing capabilities of the team by developing and implementing advanced NLP models for various applications. Key Responsibility: - Develop and improve NLP models for tasks such as sentiment analysis, text classification, and named entity recognition. - Work with large datasets of text and speech data. - Evaluate model performance and identify areas for improvement. - Collaborate closely with engineers and product managers. Qualification Required: - Master's or PhD degree in Computer Science, Linguistics, or a related field. - Strong experience with NLP frameworks and libraries. - Proficiency in Python or other programming languages. - Strong understanding of NLP algorithms and techniques. Additional Details: The company offers a competitive salary and benefits package, opportunities for professional growth and development, and a dynamic and collaborative work environment. A typical day in this role might involve data exploration, model training, and collaboration with other data scientists. Role Overview: You will play a pivotal role in enhancing the natural language processing capabilities of the team by developing and implementing advanced NLP models for various applications. Key Responsibility: - Develop and improve NLP models for tasks such as sentiment analysis, text classification, and named entity recognition. - Work with large datasets of text and speech data. - Evaluate model performance and identify areas for improvement. - Collaborate closely with engineers and product managers. Qualification Required: - Master's or PhD degree in Computer Science, Linguistics, or a related field. - Strong experience with NLP frameworks and libraries. - Proficiency in Python or other programming languages. - Strong understanding of NLP algorithms and techniques. Additional Details: The company offers a competitive salary and benefits package, opportunities for professional growth and development, and a dynamic and collaborative work environment. A typical day in this role might involve data exploration, model training, and collaboration with other data scientists.