I am a Data Analyst Fresher, passionate about turning complex datasets into clear, actionable insights. With a foundation in statistics and hands-on experience in Python, SQL, and Power BI, I focus on solving business problems through data analysis and visualization.
I am continuously enhancing my skills in data analysis and visualization, focusing on solving real world business problems using data. I also have hands on experience with Machine Learning and foundational AI, allowing me to extend beyond traditional analysis when required. I believe data delivers the most value when it is transformed into clear, actionable insights.
Goal: To analyze and optimize data pipelines and datasets to deliver accurate, scalable, and decision-ready insights.
A few problems I've turned into solutions
Built an ETL & analytics pipeline on 100K+ records & ~7K brands, uncovering 199 high-margin low-sales brands, $2.71M unsold inventory, and delivering a dashboard with $441M sales, $134M profit & ~70% cost reduction insights.
Processed 500+ CSVs (~1M+ rows) using Python, engineering 15+ financial features with NIFTY50 integration. Developed a 5-factor ranking model, backtested over 250+ days, and implemented Random Forest (~X% accuracy).
Developed a Netflix-style recommendation system using SVD on 24M+ ratings from 470K users, applying data filtering, memory optimization (~65% reduction), and hyperparameter tuning to generate personalized movie recommendations.
The tools I use to build, train, and deploy
My full experience, education, and achievements — compiled and ready to review.
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I'm always open to discussing new projects, creative ideas, or opportunities to be part of something impactful.