Clustering Project – Customer Review Segmentation
Applied unsupervised learning using K-means to group customer reviews based on sentiment and keyword patterns. Performed text preprocessing, TF-IDF feature extraction, and cluster visualization.
Analytical and detail-oriented B.Tech graduate in Computer Science with experience in data analysis, reporting, dashboard development, and business insights.
Jus Jumpin
Apr 2026 – May 2026
Analyzed, cleaned, and validated business data using SQL, Excel, and Python; developed Power BI dashboards and reports; conducted trend analysis; and delivered insights to support business decision-making while collaborating with cross-functional teams.
Bachelor of Technology (B.Tech), Computer Science
Sep 2022 – July 2026
CGPA: 7.98
Senior Secondary School
July 2021 – July 2022
Percentage: 80.4%
Secondary School
April 2019 – July 2020
Percentage: 84.8%
Applied unsupervised learning using K-means to group customer reviews based on sentiment and keyword patterns. Performed text preprocessing, TF-IDF feature extraction, and cluster visualization.
Developed a CNN-based image classification model to identify flower species and built a Streamlit web application displaying the predicted flower name and description.
Created an interactive dashboard to analyze sales performance, outlet trends, and product category insights using Power Query for data transformation and DAX for custom KPI metrics.
Analyzed sales and customer behavior using complex SQL queries on a music store database and generated insights on top-selling genres, customer segments, and purchase patterns.