This repository contains results of the completed tasks for the Quantium Data Analytics Virtual Experience Program by Forage, designed to replicate life in the Retail Analytics and Strategy team at Quantium, using Python.

This repository contains all lab work and digital assessments from the Winter Semester of my M.Sc. Data Science program at VIT Vellore. Projects span across machine learning, data mining, statistical inference, time series analysis, data visualization, and Java programming—implemented using tools like Python, R, Power BI, Tableau, Excel, and Java

Mutual Fund Analysis Dashboard using Python, Excel, and Power BI | Top 30 Low-Risk High-Return Schemes Identified

In this project, I analyze commercial sales data using NumPy and pandas. I visualize total revenue per product using color-coded bar charts in Matplotlib. It’s a foundational step in business data analysis and project documentation.

Portfolio Risk Simulator is an interactive web app that lets users build portfolios, analyze risk with VaR and Sharpe ratios, visualize correlations, and compare performance to benchmarks, uses real-time data.

End-to-end Python notebook that engineers a proxy “bad-client” label, explores drivers of credit risk, and builds a leakage-free XGBoost scorecard with threshold tuning and cross-validation.

End-to-end KYC/AML compliance data analysis using mock datasets. Includes customer risk scoring, suspicious transaction flagging, and compliance reporting in Python (Pandas, Matplotlib).

modeling of pricing and analysis of stock and options

NLP-driven sentiment analysis on financial news headlines to reveal patterns and correlations with stock price fluctuations, powering data-driven investment predictions.

This project involves a comprehensive data analysis of stock market trends and performance. The analysis aims to uncover patterns, trends, and insights that can aid in making informed investment decisions. By leveraging various data analytics techniques, this project provides valuable visualizations and interpretations of stock market data.

This project documents the development of a Python-based Forex trading algorithm that integrates technical indicators and news analytics to automate trading strategies on MetaTrader 5.

🚀 AlphaCrew: Production-grade multi-agent hedge fund platform powered by CrewAI Enterprise. Features live trading via Alpaca, real-time performance monitoring with Grafana, and human oversight through Slack. Built for sophisticated algorithmic trading and portfolio management.

This project uses data analytics and machine learning to assess and predict credit risk. It includes data preprocessing, exploratory analysis, feature engineering, and model building with Python, Pandas, and Scikit-learn to help financial institutions make informed decisions.

💰💹 A personal finance companion born from Mint's closure - designed to simply show you where your money is going with Plaid integration, personalized insights, and a custom Centi Score algorithm.

AI-powered personal budget tracker with natural language processing for expense logging, smart analytics, and personalized money-saving recommendations

🏦 Loan Approval Prediction App using Python, Scikit-learn & Streamlit — includes full EDA, feature engineering, model training, and deployment as an interactive web app.

Full-stack pipeline to detect U.S. housing market bubbles and forecast price trends. Merges 6+ macroeconomic datasets in Snowflake to compute risk scores and price predictions using walk-forward ML models. Deployed with Streamlit for interactive insights.

A full-stack finance dashboard application with machine learning insights. Features interactive KPI visualization, responsive design, and real-time financial data analytics built with React, Node.js, and MongoDB.