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sukantsaumya/README.md

👋 Hi there, I'm Sukant Saumya

Holopin badges Typing SVG

🌐 About Me

Welcome to my digital space! I'm a developer and aspiring Quantitative Analyst from Patna, India, currently pursuing a B.Tech in Computer Science at VIT-AP. My passion lies at the intersection of finance and technology — where I apply statistical modeling, machine learning, and software engineering to solve complex financial problems.

🚀 Core Competencies

📈 Quantitative Finance & Analysis

Building and backtesting systematic trading strategies, modeling financial instruments, and analyzing market data to extract alpha.

Core Skills: Python (Pandas, NumPy, Scikit-learn, Statsmodels), Time Series Analysis, Monte Carlo Simulations, Statistical Arbitrage, Risk Management (VaR, Greeks)

💻 Software & Data Engineering

Designing scalable, high-performance software and data-driven solutions using modern frameworks and cloud-native tools.

Core Skills: Java, Flutter, SQL, Firebase, REST APIs, Git, Docker, Clean Architecture

💡 Featured Projects

💻 StatArb Pro — Quantitative Pairs Trading Platform

  • Description: A full-stack platform for discovering, backtesting, and visualizing statistical arbitrage strategies.
  • Tech Stack: Python Flask Pandas Statsmodels Plotly yfinance HTML/CSS
  • Highlights:
    • Implements Engle-Granger and Johansen cointegration tests for robust pair selection.
    • Provides a responsive web dashboard with multi-market (S&P 500, FTSE 100, DAX) screeners.
    • Generates detailed, interactive HTML backtest reports with charts, trade logs, and performance metrics.

📈 Fixed Income Analytics — Yield Curve Modeling

  • Description: Constructed and calibrated the USD Treasury yield curve using the Nelson-Siegel model to price off-the-run bonds and uncover relative value opportunities.
  • Tech Stack: Python Pandas NumPy Scikit-learn Matplotlib
  • Impact: Achieved an RMSE < 4 bps and modeled over 75% of the variance in 10-year Treasury yields.

🎯 Visual Read Assist Device

  • Description: A Raspberry Pi–based assistive system converting printed text into real-time speech for visually impaired users.
  • Tech Stack: Python Tesseract OCR Text-to-Speech OpenCV
  • Impact: Enables independent access to printed text, empowering visually impaired individuals.

🛠️ Tech Stack

Languages & Databases

Frameworks & Libraries

Tools & Platforms

📊 GitHub Analytics

🔍 Currently Exploring

Quantitative Finance AI & ML Systems Development
High-Frequency Trading MLOps & Production ML Low-Latency Systems (C++)
Derivatives Pricing Models Self-Hosted LLMs (Ollama) WebAssembly
Volatility Surface Modeling Edge AI & TinyML Cloud-Native Architecture
Factor Investing Federated Learning System Design Patterns

📫 Connect With Me


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