Time Series Analysis and Forecasting for Multiple Product Variants – Conducted comprehensive data preprocessing and merging of multiple datasets, including product sales data and external economic indicators, ensuring data integrity and consistency– Utilized advanced time series analysis techniques such as Autocorrelation Function, partial autocorrelation Function, and Seasonal Decomposition to understand underlying patterns and trends in product demand– Employed feature selection methods, including Random Forest Regressors, to identify significant variables driving product sales variations across different product variants and sizes– Implemented SARIMAX modeling with grid search optimization to forecast future product demand, selecting optimal model parameters based on AIC, BIC, and error metrics for accurate predictions– Produced insightful visualizations and stored forecasted values for multiple product variants in CSV files, enabling informed decision-making and strategic planning for inventory management and resource allocation SME Banking Scorecard Development– Spearheaded the development of SME Banking Generic Scorecard and Project Plan, ensuring alignment with business objectives and constraints– Orchestrated discussions to define modeling objectives and segmentation schemes, fostering collaboration across teams for transparent and effective implementation Web Scraping, Data Preparation and Sentiment Analysis using NLP– Engineered Python scripts for efficient news retrieval and sentiment analysis using Google News API, enhancing data accessibility and processing capabilities– Conducted sentiment analysis on news articles using BERT models, categorizing sentiments accurately and organizing insights for strategic decision-making

Elected unanimously to represent the interest of 35+ post-graduate students in the Institute Placement Committee-Assisting in the placement of 1900+ students by working as a liaison between the placement office and the students -Strategized Plan of Action, including 20+ preparatory activities to enhance the placement preparation of the students Responsible for the resume verification of 120+ students and expertise company pitching for maximum recruitment

Web Scraping and Text Analysis of JOB Postings using NLP in Python – Conducted web scraping on Indeed and Glassdoor, followed by text analysis using various methods including rule-based matching, word2vec, contextualized topic modeling, and BERT named entity recognition (NER)– Developed a pipeline for skill extraction from job postings using word-level tokenization and pre-trained/fine-tuned BERT models, achieving an 85.45% accuracy in identifying top required skills– Leveraged text analysis techniques to generate word clouds representing top skills from job descriptions, demonstrating proficiency in data collection, analysis, and visualization for talent acquisition