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CHRIST (Deemed to be University)
Data Scientist
June 16, 2026 – Present
SEO-Sensei-Intelligent-Web-Content-Quality-Duplicate-Detector
November 3, 2025 – November 3, 2025
AI-powered NLP pipeline that analyzes SEO content, detects duplicates, and scores web page quality using readability metrics and machine learning.
View ProjectIndian-Snack-Image-Classifier
August 20, 2025 – November 3, 2025
This repository features a CNN-based image classifier built with TensorFlow and Keras to categorize three Indian snacks: bonda, vada, and cutlet. It includes the model's Python code, the raw dataset, and an augmented version. The project demonstrates a complete image classification workflow with data augmentation and performance metrics.
View ProjectSmart-Expense-Tracker-A-User-Friendly-Financial-Management-System-Using-Java-Programming
August 20, 2025 – August 20, 2025
Smart Expense Tracker is a Java Swing app for managing personal expenses. It lets users add, delete, filter, and view records with validations on inputs and dates. Features include expense statistics, date-based filtering, dark theme UI, and robust error handling, ensuring a reliable and user-friendly tool.
View ProjectTime-Series-Analysis-App-Using-R-Shinny
April 4, 2025 – April 4, 2025
An interactive R Shiny app for time series analysis using CSV/XLSX data. Features ADF test, ACF/PACF, smoothing, SARIMA, GARCH models, and PDF report generation. Built with ggplot2, forecast, tseries, and more. Simple UI for users with no coding skills. Open-source and easy to run locally.
View ProjectTime_series_analysis-R-Sinnny
April 4, 2025 – April 4, 2025
An interactive R Shiny app for time series analysis using CSV/XLSX data. Features ADF test, ACF/PACF, smoothing, SARIMA, GARCH models, and PDF report generation. Built with ggplot2, forecast, tseries, and more. Simple UI for users with no coding skills. Open-source and easy to run locally.
View ProjectCultural Fit Analysis
The candidate's projects are primarily personal and academic, showcasing a strong interest in data science and machine learning. The diversity of projects (time series, NLP, image classification, financial management) indicates a broad technical curiosity. However, the lack of professional experience beyond a future-dated role makes it difficult to assess cultural fit within a corporate environment. The target role is 'Data Scientist', which aligns well with the candidate's project portfolio.
Soft Skills & Operational Fit
The candidate's project descriptions suggest an ability to develop user-friendly applications and a focus on practical problem-solving. However, without psychometric test results or interview data, it is difficult to assess soft skills like teamwork, communication, or stress handling.