natural language processing data scientist.

·         Design, develop, and deploy state-of-the-art NLP models, including sentiment analysis, language translation, chatbots, text summarization, and entity recognition.
·         Oversee the collection and preprocessing of textual data, ensuring data quality and relevance for NLP tasks.
·         Innovate, keep abreast of industry trends and competition grasping new LLM architectures and technologies.
·         Resolve ambiguous and complex business problems/asks into simple technical systems that can be worked by the team.
·         Responsible for quick POC’s to evaluate the NLP solution before productionizing.
·         Design, develop, and deploy advanced NLP models, including but not limited to Word2Vec, deep learning, LLM and natural language processing (NLP) models.
·         Ensure models are scalable, maintainable, and align with the organization's goals.
·         Lead and mentor a team of data scientists, providing guidance on best practices, methodologies, and innovative solutions.
What will you have:
·         Candidate should have 7+ years of industry experience with at least 5 years of experience as a Data Scientist.
·         Bachelor’s or master’s degree in computer science, data science, artificial intelligence, or a related field.
·         Experience in building real world AI solutions/products.
·         Strong programming skills in languages like Python.
·         Proficiency in NLP frameworks and libraries, such as spaCy, NLTK, Transformers (Hugging Face), and deep learning techniques for text analysis.
·         Strong understanding of NER, POS tagging, tokenization, stemming, lemmatization, and other text preprocessing techniques.
·         Solid understanding of linear algebra, calculus, and statistics, which are foundational to machine learning.
·         Experience in developing microservices and containerized application.
·         Competence to work Independently and able understand and suggest Model Architectural changes based on the cost implications of the cloud infrastructure.
·         Highly motivated, able to work proficiently both independently and in a team environment.
·         Experience with Azure and AWS ML services is preferred.
·         Effective communication of ideas and information, both verbally and design documents where necessary.
·         Experience with source control management systems (GitHub) and continuous integration/deployment environments.
·         Should be able to mentor/drive junior team members to achieve desired outcome.