Data Scientist with a deep passion for learning and exploration.
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Causality_Detection_in_High-Dimensional_Time_Series
May 21, 2026 – Present
This repo contains implementation of a rank-based causality detection framework for high-dimensional time series inspired by research on Information Imbalance. In this project I am trying to reproduce the paper’s methods and will apply them to real-world datasets for nonlinear causal analysis..
View ProjectQuantitative-Market-Regime-Clustering-using-Return-and-Volatility
May 14, 2026 – Present
Return, volatility, and risk-regime analysis of NSE stocks using KMeans, Gaussian Mixture Models, PCA, and interactive visualizations to identify hidden market structures, cluster financial assets by behavior, and study relationships between risk, return, and market dynamics.
View ProjectNeuroScan_AI_-_Deep_Learning_for_Brain_Tumor_Recognition
May 7, 2026 – Present
This is deep learning project focused on detecting and classifying brain tumors from MRI scans. It helps identify different tumor types through automated image analysis, supporting faster medical interpretation and AI-driven healthcare research.
View ProjectLectureAI_-_Personal_Lecture_Assistant
April 28, 2026 – Present
This project "LectureAI" turns lecture videos into an interactive learning experience, helping users quickly find concepts, understand content better, and assess their knowledge without wasting time.
View ProjectSpread_Z-Score_-_Statistical_Arbitrage_Strategy
March 9, 2026 – Present
Statistical arbitrage strategy using Z-score normalization on implied volatility spread between BankNifty and Nifty. It identifies mean-reverting deviations to generate trading signals, significantly improving risk-adjusted returns compared to baseline strategies under realistic market conditions.
View ProjectMinimum_Variance_Portfolio_Optimization
March 3, 2026 – Present
Portfolio Optimization project to build and compare different ways to create low-risk investment portfolios. It studies how different approaches perform over time and shows how balancing risk, stability, and diversification can lead to more practical and reliable investment decisions.
View ProjectQuantPulse_Short-term-Portfolio-Optimizer
December 17, 2025 – Present
ML driven short-term portfolio optimization system that predicts asset prices and dynamically constructs portfolios. It combines rolling price forecasts with adaptive risk-return estimation using Efficient Frontier, Bayesian optimization, and HERC to enable responsive, data-driven trading decisions.
View ProjectAPortfolio
June 12, 2025 – Present
An interactive Streamlit-based portfolio website powered by an agentic AI assistant. It uses LLMs, LangChain, and RAG to enable real-time, conversational exploration of projects, skills, and experience, transforming a static portfolio into a dynamic and personalized user experience.
View ProjectCreditRisk-Predicting-Borrower-Reliability
January 11, 2025 – Present
Machine Learning project that predicts whether a person may fail to repay credit card dues based on their profile and past behavior. It compares different approaches to find the most reliable one, helping banks make safer lending decisions and reduce financial risk.
View ProjectFrom-Data-to-Dwellings-Decoding-Amsterdam-s-Housing-Prices
October 7, 2024 – September 21, 2025
Data Analysis project for housing prices in Amsterdam by studying factors like house size, number of rooms, and location. It uncovers key trends and relationships to help understand what drives property prices and supports better buying or investment decisions.
View ProjectCultural Fit Analysis
The candidate's project portfolio shows a strong inclination towards quantitative finance and machine learning applications, which aligns well with a data scientist role. The diversity of projects, from financial modeling to AI assistants and medical imaging, suggests adaptability and a broad interest in applying data science across different domains. However, the lack of team-based projects or professional experience makes it difficult to fully assess cultural fit in a collaborative environment.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions indicate an ability to work on complex problems independently.