Hi, I’m Daksh. I am a Data Science and Full-Stack Developer specializing in building production-ready AI applications, quantitative trading systems, and real-time automated workflows. I bridge the gap between complex algorithmic logic and clean, scalable software architecture.
Whether you need to extract predictive insights from data, train and optimize machine learning models, or build seamless API integrations, I focus on delivering robust, investor-ready, and production-grade MVPs.
Core Technical Stack:
Data Science & AI: Python, Pandas, NumPy, Scikit-Learn, XGBoost, LightGBM, Hugging Face Transformers.
Quantitative Engineering: Backtesting frameworks, Pine Script (v5/v6), statistical validation, multi-factor modeling.
Full-Stack & APIs: FastAPI, SQL (PostgreSQL/MySQL), Node.js, Webhooks, Meta/WhatsApp Business Cloud APIs.
Dashboards & Visualization: Power BI, Tableau, interactive frontend UI design.
My Engineering Philosophy:
Objectivity First: No subjective assumptions. Every model, trading script, or analytics dashboard I build is grounded in statistical validation and clear empirical data.
Clean Architecture: I write modular, well-documented, and extensible code that is easy to deploy, scale, and maintain.
Real-World Value: I specialize in building practical, end-to-end applications (from intelligent scoring models to automated real-time notification systems) designed to solve concrete problems.
Let’s connect to turn your conceptual roadmap into a high-performance, working reality.