🚀 Building scalable AI systems and data-driven architectures.
👋 Hi, I'm Tanuj Bhardwaj
🚀 Passionate about building intelligent systems, data-driven products, and scalable analytics solutions.
- 🤖 AI-powered applications & LLM-based systems
- 📊 Data analytics pipelines & real-world ML models
- 🧠 Algorithmic trading & async event-driven architectures
- 🏗️ End-to-end ML systems (data → model → deployment)
- 🧠 Applied Machine Learning & Deep Learning projects
- 📈 Data Science research & experimentation
- ⚡ AI-driven automation tools
- 📊 Analytics dashboards & decision intelligence systems
- 🔬 Advanced MLOps & model deployment at scale
- 🧩 Distributed AI systems & high-performance computing
- 📡 Production-grade data engineering workflows
- 🧠 Advanced Deep Learning architectures
- 📊 Statistical modeling & optimization
- 🔎 Feature engineering & model interpretability
- ⚙️ Scalable data systems & real-time processing
- 📊 Data Analytics & Visualization
- 🤖 Machine Learning algorithms
- 📈 Predictive modeling
- 🐍 Python for AI & data pipelines
- 🧠 Algorithmic problem solving
I enjoy turning raw, messy datasets into structured insights and intelligent systems that actually make decisions.
- Event-driven architecture
- Non-blocking execution
- Risk management module
- Structured logging
- End-to-end ML pipelines
- Model optimization & evaluation
- LLM-based experimentation
- ETL pipelines
- SQL/NoSQL modeling
- Dashboard integration
- Exploratory Data Analysis (EDA) pipelines
- Statistical modeling & hypothesis testing
- KPI design & business metric tracking
- Interactive dashboards (Power BI / Plotly)
- Decision-support analytics systems
- Built ML models with production-level evaluation pipelines
- Designed async systems with non-blocking execution logic
- Processed large-scale structured datasets
- Deployed APIs using FastAPI & Docker
- Designed analytics dashboards for actionable insights
- Performed large-scale data cleaning & transformation
- Built statistical validation frameworks for model evaluation
- Developed metric-driven experimentation workflows
- Prefer async, event-driven architectures
- Build production-first ML systems
- Focus on scalability & observability
- Treat data as a product
- Design analytics systems that drive measurable business decisions