Nikitha R

Conducted EDA on the Water Potability dataset (3,276 samples, 9 physicochemical features), handling missing values via mean imputation and identifying key drivers using KDE plots, pairplots, and a correlation heatmap. Built and evaluated a Linear Regression model on Bangalore rainfall data using StandardScaler and an 80/20 train-test split, validating fit with actual-vs-predicted and residual anal

Developed and maintained a scalable discount-aggregation platform using the MERN stack and implemented Python web-scraping pipelines (BeautifulSoup, Scrapy) to fetch verified deals from multiple e-commerce sources. Automated CI/CD with GitHub Actions, containerized services with Docker, and deployed on Kubernetes and Vercel to ensure high availability and performance.

Performed end-to-end attrition analysis on the IBM Employee Dataset, identifying key drivers of turnover and delivering insights that reduced potential turnover risk by 20%. Built and optimized a Decision Tree classifier using Python, Pandas, scikit-learn and Matplotlib, improving prediction accuracy by 30% through hyperparameter tuning and cross-validation.

Built an end-to-end ML pipeline in Python (Pandas, scikit-learn) on the IBM HR dataset (1,470 records, 35 features) with IQR outlier removal and correlation-driven feature selection to identify key attrition drivers. Tuned a Decision Tree using GridSearchCV with 5-fold cross-validation, improving accuracy by 30% and reducing false-negative attrition predictions.

Engaged in the IISc Applied ML program (online), performing EDA and building/evaluating a Linear Regression pipeline for water potability prediction.

Grade: 8.6

Activities and societies: Participated in national and institute-level hackathons (Byte Synergy, Codeathon, Ideathon); volunteered at Smart India Hackathon 2023 on a blood-donation app (improved availability by 20%); NSS student volunteer at RIT (2021–2023), leading community initiatives impacting 500+ people.

Bachelor of Engineering in Information Science at M. S. Ramaiah Institute of Technology (Bangalore) from 2021 to 2025 with a CGPA of 8.6.

Grade: CGPA: 8.6

Activities and societies: Competed in national/institute-level hackathons (IIIT-B Byte Synergy, RIT Ideathon, BMSCE Codeathon). Volunteered at Smart India Hackathon 2023 and NSS (2021–23).

Pursued a Bachelor of Engineering in Information Science at MS Ramaiah Institute of Technology (2021–2025), achieving a CGPA of 8.6.