Data Scientist - NLP/Generative AI (6-8 yrs)

We are seeking a highly skilled and motivated Data Scientist with expertise in Natural Language Processing (NLP), Python, and Generative AI (GenAI) to join our dynamic team. The ideal candidate will design, develop, and deploy cutting-edge solutions leveraging tools such as nltk, spaCy, and other modern NLP frameworks. Experience in prompt engineering for GenAI models (e.g., GPT, LLaMA) is crucial.

You will play a key role in solving business problems by building models, extracting insights from text data, and fine-tuning Generative AI solutions to deliver impactful results.

Key Responsibilities :

- Design and implement NLP models and pipelines for tasks such as text classification, sentiment analysis, named entity recognition (NER), text summarization, and topic modeling.

- Develop and optimize Generative AI solutions by leveraging tools like OpenAI's GPT, BERT, LLaMA, or other LLM-based frameworks.

- Perform prompt engineering to maximize the performance of generative models for various applications (e.g., content generation, chatbot development, and question-answering systems).

- Preprocess and analyze large-scale unstructured text datasets to extract meaningful insights.

- Collaborate with cross-functional teams, including data engineers, product managers, and software developers, to deploy AI/ML solutions in production.

- Design robust, scalable solutions using Python libraries such as nltk, spaCy, Hugging Face Transformers, PyTorch, or TensorFlow.

- Continuously research and experiment with emerging trends and state-of-the-art methods in NLP, LLMs, and Generative AI.

- Document processes, tools, and solutions while maintaining best practices for reproducibility and scalability.

Required Skills & Qualifications :

- Bachelor's/Master's degree in Computer Science, Data Science, Artificial Intelligence, or a related field.

- 3+ years of experience as a Data Scientist, with a focus on Natural Language Processing (NLP) and Generative AI.

- Proficiency in Python programming and libraries/tools, including : nltk, spaCy, Hugging Face Transformers, Scikit-Learn, TensorFlow, PyTorch.

- Experience in prompt engineering and fine-tuning pre-trained models (e.g., GPT, BERT, T5, LLaMA).

- Strong understanding of NLP tasks: tokenization, embeddings, sentiment analysis, NER, summarization, etc.

- Familiarity with large language models (LLMs) and their practical deployment in real-world applications.

- Hands-on experience with cloud platforms like AWS, Azure, or GCP is a plus.

- Proficiency with data visualization tools (e.g., Matplotlib, Seaborn) and understanding of data preprocessing techniques.

- Strong problem-solving skills, creativity, and analytical thinking.