Insight-Driven Decision Making

I apply data science techniques to uncover patterns, build models, and power intelligent systems. With expertise in Python, Pandas, SQL, and visualization libraries, I help transform raw data into actionable insights used in real-world solutions.

Transforming Complex Data into Scalable Solutions

My work in data science spans from exploratory data analysis to full-stack deployments. I've built intelligent solutions like a perfume recommendation system, AI-based healthcare web app, and interactive dashboards — integrating machine learning with real-world use cases.

• Hands-on experience in data cleaning, feature engineering, and visualization using Seaborn, Matplotlib, and Plotly.
• Built scalable ML pipelines using FastAPI, Streamlit, and MLflow with deployment on AWS & monitoring via Prometheus.
• Proficient in real-time insights, analytics dashboards, and RESTful API integrations for data apps.

I combine statistical thinking with practical engineering to deliver meaningful data solutions. My approach involves breaking down complex problems into interpretable insights, tested models, and responsive interfaces.

Whether it's labeling datasets, building NLP-based systems, or analyzing user behavior, I strive to build systems that are not only technically sound but also user-focused and impact-driven.