I am a final-year AI & ML engineering graduate with hands-on experience in data analysis, machine learning, and business intelligence.
I have worked on end-to-end analytics workflows, including data cleaning, preprocessing, exploratory data analysis, feature engineering, and model development.
My experience includes building SQL databases, designing ETL pipelines, and creating interactive Power BI dashboards for reporting and decision-making.
I have also applied GenAI concepts to analytics workflows, including natural language querying and insight generation for business reporting.
Through internships and projects, I have developed a strong ability to translate raw data into clear, actionable insights for stakeholders.
I am looking for opportunities where I can contribute as a data analyst or in a related analytics role while continuing to grow in AI, machine learning, and business intelligence.
Conducted AI-based data analysis on real-world datasets using Python libraries such as Pandas, NumPy, and Matplotlib. Developed and evaluated machine learning models for prediction and classification tasks. Performed data preprocessing, feature engineering, and exploratory data analysis. Assisted in building intelligent, data-driven applications for business use cases.
Built a mutual fund analytics platform with an ETL pipeline and a SQLite star-schema database. Performed exploratory data analysis and created 15+ visualizations to surface fund performance trends. Calculated Sharpe Ratio, Sortino Ratio, Alpha, Beta, CAGR, VaR, and CVaR. Built an interactive Power BI dashboard and a fund recommendation engine.
B.E., Artificial Intelligence & Machine Learning
Final-year engineering degree in Artificial Intelligence & Machine Learning with CGPA 6.54.
Pre-University Science (PUC), Science
Completed pre-university science education with 64.3%.
SSLC
Completed secondary school education with 59.52%.
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