Data Scientist with expertise in NLP, Generative AI, RAG, Deep Learning, and AWS

Natural Language Processing
Specialized in NLP with expertise in text classification, aspect-based sentiment analysis, and named entity recognition. Built robust NLP systems using BERT, Transformers, and spaCy.

Deep Learning
Development and tuning of deep learning models using CNNs, LSTMs, and BERT for visual and textual data. Experience with TensorFlow, Keras, PyTorch, and NLTK frameworks.

Cloud & Deployment
Integration of ML models into APIs using Flask and deployment via cloud infrastructure. Proficient with AWS S3, EC2, SageMaker, Bedrock, and Git for model deployment.

Machine Learning
Implementation of various ML algorithms including Linear Regression, Logistic Regression, Decision Tree, Random Forest, SVM, KNN, and boosting algorithms.

Generative AI
Experience with Gen AI, RAG, fine-tuning pretrained models, LLMs, prompt engineering, and LangChain. Built generative AI chatbots using Retrieval-Augmented Generation.

Data Engineering
Development of end-to-end pipelines for predictive analysis, image-based defect detection, and NLP-driven complaint classification.

Programming & Tools
Proficiency in Python, SQL, and various libraries including NumPy, Pandas, SciPy, Scikit-learn. Experience with Linux, Windows, GitHub, Anaconda, JIRA, and Agile methodology.