Analyst
-Authored and curated content on a data science project for the lab portal, resulting in a 10% increase in user engagement and knowledge dissemination. -Data Mining and NLP Project in Python: Developed a Python script using WhisperAI, enabling efficient scraping of 500 hours of audio data, improving data collection speed by 40%. Optimized text data analysis by using Named Entity Recognition (NER) techniques, increasing entity recognition accuracy by 25% and reducing processing time by 30%. Achieved 63% accuracy in predicting audiobook views by using Linear Regression models. Visualized 10 key insights into audiobook consumption trends by using Tableau dashboards. -Classification Project in Python and R: Collaborated with the faculty and another lab assistant to identify and work on a data science project, to build a model to predict the class of the patients in a pelvic study, classifying them into ‘normal’ and ‘abnormal’ based on factors such as pelvic tilt, incidence etc. Responsible for feature selection and application of K-Nearest Neighbors algorithm with 77% accuracy. Deployed Random Forest Classifier algorithm to increase accuracy of prediction by 11%.
