I am a detail-oriented Data Analyst with skills in data cleaning, visualization, and statistical analysis using Python (Pandas, NumPy), SQL, and Excel. With a background in Computer Science and Business Systems, I combin…
I am a detail-oriented Data Analyst with skills in data cleaning, visualization, and statistical analysis using Python (Pandas, NumPy), SQL, and Excel. With a background in Computer Science and Business Systems, I combine technical expertise with business understanding to turn complex data into clear, actionable insights.
Passionate about data-driven problem solving, I enjoy building dashboards, reports, and applications that support smarter decision-making. Currently focused on growing as a Data Analyst, I aim to apply my skills to real-world projects that create impact.
Covered the full data processing workflow using Python, SQL, and BI tools.
Built a churn model reaching 92% accuracy using Scikit-learn.
Created Power BI reports for customer behaviour and retention data.
Developed ETL scripts for handling 100K+ telecom records.
Practised dataset cleaning and generating automated summaries.
• Developed an interactive ML web app to predict customer churn with 95% accuracy using Logistic Regression and Random Forest. • Automated ETL pipeline handling 10,000+ telecom customer records for churn behavior analysis. • Built 4+ dynamic dashboards in Streamlit and Plotly for customer segmentation and retention trends. • Improved churn prediction precision by 22% after hyperparameter tuning and ROC-AUC optimization. • Deployed complete application on Streamlit Cloud, enabling real-time customer churn prediction.
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