CS Undergrad @ NIET | Full-Stack Developer (Java/Spring Boot/React) | Passionate about building AI-driven solutions and solving complex DSA problems.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
NBA-Advanced-Analytics
May 15, 2026 – Present
An enterprise-grade NBA Advanced Analytics Dashboard. Built with R Shiny, utilizing unsupervised Machine Learning (K-Means) and custom efficiency metrics (TS%, eFG%) to evaluate player archetypes.
View Project-CareerPilot
May 7, 2026 – Present
AI-powered career platform with mock interviews, adaptive quizzes, and RAG-based semantic search. Built with Java, Spring Boot, React.js, PostgreSQL & Redis.
View ProjectEcommerce-Multivendor
September 16, 2025 – Present
A simple multivendor e-commerce application built with PHP (procedural + mysqli), Bootstrap, and plain JS.
View ProjectAutomated-Resume-Screening
May 13, 2025 – Present
We propose an Al-powered Resume Screening Application that automates the screening process using Machine Learning and Natural Language Processing. The system provides objective evaluation, detailed candidate feedback, and comprehensive skill analysis while supporting multiple file formats.
View ProjectTax-Calculation-System
April 10, 2025 – Present
This project is an automated tax calculation system designed to help users calculate their income tax based on Indian tax laws. It provides both salaried and self-employed individuals with a simple and efficient way to calculate taxes based on the latest Indian tax regimes. The system is built using Node.js, Express.js, MongoDB, and React.js.
View ProjectCultural Fit Analysis
The candidate shows a strong inclination towards personal projects, demonstrating initiative and self-learning. However, the project diversity, while broad in technology, does not consistently align with a senior Data Scientist role, indicating a potential gap in focused, advanced data science applications beyond basic ML. The 'experienceLevel' is 0, which suggests a lack of professional experience, potentially impacting cultural fit for a senior role requiring established team collaboration and industry practices.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The psychometric test score is 0, providing no insights.