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I transform raw data into actionable decisions through Data Science, Analytics, Python, SQL, Machine Learning, and AI turning complex problems into intelligent
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Data Scientist
June 19, 2026 – Present
NeuraFlow-AI
June 1, 2026 – Present
Production-grade Multi-LLM AI Agent Platform integrating Gemini, Groq, OpenRouter, and Hugging Face. Features intelligent task routing, automatic fallback handling, PDF document Q&A, AI decision tracing, provider analytics, and a modern Streamlit interface. Built with Python, GenAI, NLP, and scalable architecture.
View ProjectAI-Trading-Coach
April 25, 2026 – Present
AI-powered trading psychology coach that analyzes trader behavior, detects patterns (FOMO, overtrading, revenge trading), and delivers real-time, explainable coaching using a persistent memory system and evaluation metrics.
View ProjectCodeAlpha-Data-Science-Projects
April 16, 2026 – Present
This repository contains 3 Data Science projects completed as part of the CodeAlpha Internship: 1. Unemployment Analysis using Python 2. Sales Prediction using Machine Learning 3. Car Price Prediction using Regression Projects include data cleaning, analysis, visualization, and model building with real-world datasets.
View ProjectLast-Mile-Delivery-Optimization
April 9, 2026 – Present
Optimizing last-mile delivery using route optimization algorithms (TSP/VRP) with real-world constraints, visualization, and performance analysis.
View ProjectAdvanced-Python-Project-Ideas-for-Real-World-Applications
March 29, 2026 – Present
6 production-grade Python projects across NLP, ML, Computer Vision, IoT & System Design. Resume Screener, Stock Predictor, Face Recognition, Chat App, Recommendation Engine & IoT Automation. All verified & runnable.
View ProjectCustomer-Churn-Prediction-Action-System
February 27, 2026 – Present
End-to-end Customer Churn Prediction & Action System using Machine Learning (XGBoost, Random Forest) with SHAP explainability and a Streamlit dashboard to predict churn risk, identify key drivers, and generate actionable retention strategies for data-driven business decisions
View ProjectRAG-Based-AI
January 10, 2026 – Present
A RAG-based AI combines a language model with external information retrieval. It first fetches relevant documents from a knowledge source, then generates answers using that context. This improves accuracy, keeps responses grounded in real data, and allows dynamic updates without retraining.
View ProjectGreen-Destinations-Employee-Attrition-Analysis
January 8, 2026 – Present
🚀 Production-ready AI system for employee attrition prediction. Built with FastAPI and Streamlit, featuring high-recall modeling and SHAP-based explainability for strategic HR decision support.
View ProjectHealthy-Life-Expectancy-HALE-Analysis
December 7, 2025 – Present
Healthy Life Expectancy (HALE) measures the average number of years a person is expected to live in good health by adjusting total life expectancy for periods of illness or disability. It provides a clearer picture of population health and helps policymakers evaluate healthcare quality and outcomes.
View ProjectInterior-design-Website-
November 8, 2025 – Present
DNEST Interior Design Studio blends creativity with precision to craft modular, minimal, and functional spaces. We specialize in personalized residential and commercial interiors, guided by structured workflows, ergonomic planning, and visual clarity—delivering immersive environments that inspire and endure.
View ProjectCultural Fit Analysis
The candidate's portfolio showcases a strong passion for Data Science and AI, aligning well with an innovative and technically driven culture. The diversity of personal projects, from financial applications to HR analytics and NLP, suggests adaptability and a broad interest in applying data science to various domains. The lack of formal work experience or team-based projects makes it challenging to fully assess collaboration and cultural integration.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and self-driven individual, capable of taking initiative on complex AI/ML projects. The focus on 'production-grade' systems and explainability suggests an understanding of real-world deployment and ethical considerations. However, without formal work experience or psychometric test results, it's difficult to assess stress handling, team collaboration, or direct communication skills.