Data Scientist Lead - Generative AI

Job Description :

Responsibilities :

- Lead the development and deployment of GenAI applications, ensuring optimal performance and scalability.

- Research and implement state-of-the-art techniques for text generation, summarization, and other GenAI tasks.

- Optimize GenAI models for specific use cases and business requirements.

- Design and implement NLP solutions for various tasks, including sentiment analysis, text classification, entity recognition, and information extraction.

- Utilize NLP libraries (NLTK, spaCy, TextBlob, TensorFlow, PyTorch, Hugging Face) and pre-trained models (BERT, GPT-3, Transformers) to build robust NLP pipelines.

- Develop and maintain text preprocessing pipelines, including tokenization, part-of-speech tagging, lemmatization, stemming, and named entity recognition.

- Develop and deploy machine learning and deep learning models for various AI applications.

- Apply appropriate ML/DL techniques to solve complex business problems.

- Evaluate and optimize model performance using appropriate metrics.

- Lead and mentor a team of data scientists and engineers, providing technical guidance and fostering a collaborative environment.

- Manage stakeholder expectations and communicate project progress effectively.

- Collaborate with cross-functional teams to deliver AI-driven insights and solutions.

- Stay updated with the latest advancements in NLP, GenAI, and related fields.

- Conduct research and explore new techniques to improve AI solutions.

- Contribute to the development of intellectual property and best practices.

Must-Have Skills :

- 10+ years of mandatory experience with Generative AI (GenAI) applications.

- Proven experience in people management and stakeholder management.

- Strong expertise in Natural Language Processing (NLP).

- Proficiency in Machine Learning (ML) and Deep Learning (DL).

- Advanced programming skills in Python.

- Extensive experience with NLP libraries: NLTK, spaCy, TextBlob, TensorFlow, PyTorch, Hugging Face.

- Hands-on experience with pre-trained models: BERT, GPT-3, Transformers.

- Strong understanding of text preprocessing techniques: Tokenization, Part-of-Speech Tagging, Lemmatization, Stemming, Named Entity Recognition.

- Experience in NLP tasks: Sentiment Analysis, Text Classification, Entity Recognition.

Technical Skills :

- Text Preprocessing: Tokenization, Part-of-Speech Tagging, Lemmatization, Stemming, Named Entity Recognition.

- Machine Learning (ML).

- Natural Language Processing (NLP).

- Pre-trained Models: BERT, GPT-3, Transformers.

- GenAI.

- NLP Libraries: NLTK, spaCy, TextBlob, TensorFlow, PyTorch, Hugging Face.

- Python.

- Deep Learning (DL).

Qualifications :

- Masters or Ph.D. in Computer Science, Artificial Intelligence, or a related field.

- Proven track record of developing and deploying successful AI solutions.

- Strong analytical and problem-solving skills.

- Excellent communication and presentation skills.

- Ability to work in a fast-paced 1 and dynamic environment.

- Passion for innovation and a commitment to delivering high-quality results.