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myselfRaifMondal/README.md

👋 Hi, I'm Raif Mondal

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🚀 About Me

name: Raif Mondal
role: Founder & Quantitative Systems Architect
location: India 🇮🇳
focus: 
  - Quantitative Finance
  - High-Frequency Trading Infrastructure
  - AI/ML in Financial Markets
  - Production ML Pipelines
philosophy: "Building robust, scalable systems that operate autonomously in production"
📖 Read More About My Journey
  • 🚀 Founder & Builder creating the future of quantitative finance in India
  • 💼 Current Ventures:
    • IndiQuant — Crowdsourced intelligence platform for Indian Equity Markets (NSE/BSE)
    • Playmaker — High-Frequency Trading firm building ultra-low latency execution infrastructure
  • 🧠 Tech Stack: Python, C++, Java, R, TensorFlow, PyTorch, Real-time Data Processing, System Architecture
  • 📈 Domain Expertise: Systematic trading, quantitative research, ML/AI for financial markets, market microstructure
  • 🔭 Focus Areas: Production ML pipelines, HFT infrastructure, alternative data, risk management systems
  • 💡 Philosophy: Build robust, scalable systems that operate autonomously in production. Every solution serves measurable business objectives.
  • 🏆 Background: AI/ML Engineer, Quantitative Systems Architect, Open Source contributor
  • 🌱 Constantly pushing boundaries in RL, Generative AI, System Design, and Quantitative Strategies

💼 Current Ventures

📊 IndiQuant

Democratizing Quantitative Intelligence

Building a crowdsourced intelligence platform that brings institutional-grade quantitative research and market analytics to Indian equity markets.

Core Features:

  • 📈 Systematic trading signals for NSE/BSE
  • 🔬 Real-time market microstructure analysis
  • 💭 Sentiment aggregation & alternative data
  • 🎯 Quantitative research infrastructure

⚡ Playmaker

High-Frequency Trading Infrastructure

Developing next-generation HFT systems with focus on Indian markets and cross-border arbitrage.

Technology Stack:

  • ⚡ Sub-millisecond execution engines
  • 📊 Tick-level data processing
  • 🛡️ Advanced risk management
  • 🎯 Co-location & direct market access

🛠️ Tech Stack & Skills

Languages & Core Technologies

Python C++ Java R C

AI/ML Frameworks

TensorFlow PyTorch scikit-learn OpenCV

Data & Databases

PostgreSQL SQLite Redis Apache Kafka

Infrastructure & DevOps

Linux Docker AWS Git

🔥 Currently Building & Learning

HFT Infrastructure Production ML Distributed Systems Quant Finance

📌 Featured Projects

📊 Fundamental Financial Data Scrapper

Production-ready data acquisition system for fundamental analysis. Powers IndiQuant's data infrastructure.

Tech: Python • Web Scraping • Data Pipeline

📈 Trade-Base

Modular framework for systematic trading research with backtesting engine and risk management modules.

Tech: Python • Backtesting • Risk Management

📰 FinNews Sentiment Analysis

NLP-powered sentiment analysis for financial news. Real-time signal generation for trading systems.

Tech: NLP • PyTorch • Real-time Processing

🏦 JP Morgan Quant Projects

Quantitative research implementations: pricing models, risk analytics, and portfolio optimization.

Tech: Python • Quantitative Finance • Risk Analytics

🌌 NEO Earth Close Approaches ML

ML application demonstrating scalable data processing and predictive modeling techniques.

Tech: Machine Learning • Data Processing • Predictive Analytics

→ View All Projects

📊 GitHub Statistics

Contribution Graph

🏆 GitHub Achievements

Trophies

💬 Let's Talk About

🚀 Startup Building 📊 Quantitative Finance 🤖 AI/ML in Finance ⚡ Infrastructure
Fintech ventures Systematic trading Predictive models HFT systems
Product development Alpha generation RL for execution Low-latency architecture
Scaling teams Market microstructure Alternative data Production ML pipelines

🌐 Connect With Me

LinkedIn Instagram Gmail Twitter Portfolio

💭 Quote of the Day

"In markets as in engineering, edge comes from doing what others cannot or will not do."

Building the future, one commit at a time 🚀

Contributors

Thank you for visiting! ⭐

Pinned Loading

  1. NEO-Earth-Close-Approaches-ML NEO-Earth-Close-Approaches-ML Public

    NEOvision is an interactive visualization dashboard built with Streamlit and powered by data from NASA JPL's SBDB Close-Approach API combined with custom Machine Learning predictions. It tracks, cl…

    Jupyter Notebook

  2. FinNews-Sentiment-Analysis FinNews-Sentiment-Analysis Public

    This repository contains a Python-based sentiment analysis tool that fetches financial news from Moneycontrol and determines the sentiment of the news article. The sentiment analysis helps traders …

    Python

  3. Fundamental-Financial-Data-Scrapper Fundamental-Financial-Data-Scrapper Public

    Welcome to the Fundamental-Financial-Data-Scrapper repository! This project is designed to automate the extraction of fundamental financial data (such as balance sheets and equity reports) for list…

    Python

  4. JP-Morgan-Quant-Projects JP-Morgan-Quant-Projects Public

    This repository contains projects completed as part of JPMorgan Chase & Co.'s Quantitative Research Job Simulation via Forage. These projects focus on key aspects of financial analysis, quantitativ…

    Python

  5. Derivative-Pricing Derivative-Pricing Public

    The Black-Scholes formula is probably one of the most widely cited and used models in derivative pricing. Numerous variations and extensions of this formula are used to price many kinds of financia…

    Python