Data Science

Responsibilities: -

• design, development and implementation of NLP projects and solve complex business problems..

• Well versed with Artificial Intelligence, Machine Learning and Deep Learning algorithms and techniques.

• Evaluating and selecting appropriate machine learning models for tasks, as well as building and training working versions of those models using Python and other open-source technologies

• Proven experience in developing and deploying NER models.

• Experience with transfer learning and pre-trained language models (e.g., BERT, GPT).

• Proficiency in programming languages such as Python, with experience in NLP libraries (e.g., spaCy, NLTK, Stanford NLP, Hugging Face Transformers).

• Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch, Keras, scikit-learn, Caffe, CNTK

• Working across client teams to develop and implement LLM solutions. Develop prompts that instruct LLM to generate relevant and accurate responses, RAG Architecture, LLM Fine Tuning

• Expertise in EDA, data engineering, including data curation, cleaning, and preprocessing.

• Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions.

• Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels.

• Track record of driving innovation and staying updated with the latest AI research and advancements