Strong knowledge on Data Structures. Proficiency in Python, SQL.
Proficient in Data manipulation and cleansing (pre-process large datasets, handle missing values, perform feature engineering, ensure data integrity).
AI / ML, Strong NLP, Deep Learning Concepts, with transformer architecture understanding.
Proficiency in building and deploying models for various NLP tasks.
Natural Language Processing (NLP) : Knowledge of NLP techniques for text mining and sentiment analysis can be helpful for applications like customer feedback analysis, chatbot development, and fraud detection in written communication.
Statistical Analysis : Strong proficiency in statistical techniques and methodologies, including hypothesis testing, regression analysis, time series analysis, and 7+yrs