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dhruvil-633/README.md

💫 About Me

🔭 Quant-focused ML engineer working on HFT / MFT trading systems
📊 Building numeric–sentiment fusion models for short-horizon prediction
⚙️ Focused on low-latency, robust, and interpretable signals
🌱 Working with PyTorch / TensorFlow for research and live pipelines
🤝 Open to collaboration on quant research, HFT infra, and ML trading tools
📫 Reach me via email or LinkedIn
😄 He/Him | ⚡ Volleyball 🏐 & Badminton 🏸

🚀 Current Project

D’s Method – Numeric–Sentiment Fusion (MFT)

  • Price + volatility-based features
  • Market / index / company sentiment
  • Volatility-scaled interaction term
  • Rolling window, memory-efficient design
  • Real-time + backtest ready

🧠 Skills

Math & Stats
Probability · Linear Algebra · Optimization · Time Series · Inference

Quant Finance
Market Microstructure · Feature Engineering · Volatility Modeling · Backtesting

💻 Tech Stack

Languages

Python C C++ JavaScript R

ML / Quant Research

PyTorch TensorFlow Keras scikit-learn XGBoost LightGBM NumPy Pandas SciPy mlflow

Data Engineering & Streaming

Apache Kafka Redis RabbitMQ

Backend / Infra

Flask Django FastAPI PostgreSQL MongoDB

DevOps / Performance

Docker Linux Git GitHub Actions

Visualization & Tools

Matplotlib Plotly OpenCV Jupyter

Focus: Signal validity, robustness, and latency — not curve fitting.

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