Turning raw data into decisions that move the business.
I'm a data analytics professional who enjoys transforming complex datasets into clear, actionable business insights. I work across the analytics lifecycle - from SQL querying and Python analysis to Power BI and Tableau dashboards - helping stakeholders understand performance, identify trends, and make informed decisions.
- 🔭 Focused on data analytics, business intelligence, predictive analytics, and reporting
- 📊 Experienced with Power BI, SQL, Python, Tableau, and Excel
- 🌱 Continuously improving my skills in data modeling, automation, visualization, and machine learning
- 💬 Interested in solving business problems through data-driven analysis
| Domain | Tools |
|---|---|
| Languages | Python, SQL |
| Business Intelligence | Power BI, Tableau, Excel |
| ML / Analytics | scikit-learn, Predictive Modeling, Clustering, Regression, Time-Series |
| Data Wrangling | Pandas, NumPy, Power Query |
| Visualization | Power BI, Tableau, Matplotlib, Seaborn |
| Optimization | Google OR-Tools, Linear / Integer Programming |
| Databases | MySQL, Relational Design, Data Modeling, 3NF |
A selection of projects demonstrating practical experience in data analysis, business intelligence, predictive modeling, visualization, database design, and optimization.
Python · Pandas · scikit-learn · Machine Learning
Developed a classification model to identify customers at risk of loan default. Performed data preprocessing, exploratory analysis, feature evaluation, and model comparison, achieving a ROC-AUC score of 0.915.
Python · Pandas · Machine Learning · NLP
Analyzed application ratings and customer reviews to identify factors associated with user satisfaction. Applied sentiment analysis and compared five machine-learning models for predictive analysis.
Python · K-Means · Excel · Customer Analytics
Applied K-Means clustering to segment customers into four distinct behavioral groups and translated analytical findings into targeted marketing opportunities.
Tableau · Data Visualization · Trend Analysis
Built an interactive Tableau analysis of 14.8K+ electric vehicle registrations, examining adoption patterns, vehicle types, manufacturers, geographic trends, and BEV versus PHEV distribution.
Python · Power BI · Predictive Analytics · Prescriptive Analytics
Combined predictive modeling and business intelligence to analyze housing prices and bike-sharing demand. Developed Power BI visualizations to communicate patterns, analytical results, and decision-oriented insights.
Python · Google OR-Tools · Mixed-Integer Programming
Developed an optimization model for public transportation scheduling using Google OR-Tools, applying mixed-integer programming to evaluate operational constraints and improve resource allocation.
| Project | Focus | Technologies |
|---|---|---|
| PM2.5 Air Quality Forecasting | Time-series forecasting and environmental analytics | Python ARIMA |
| End-to-End Python Data Analysis | Data cleaning, EDA and analytical modeling | Python Pandas |
| Customer Behavior Models | Regression, classification and clustering | Python SQL Power BI |
| Car Dealership Database System | Relational database design with 9 entities and 3NF normalization | MySQL SQL |
| Uber vs Lyft Comparative Analysis | Statistical analysis of approximately 650K ride records | Python Statistics |
| PESTEL Analysis — Ethanol Blending | Policy, economic and strategic analytics | Python Analytics |
| Ethics in Prescriptive Analytics | Responsible analytics, optimization and data privacy | Optimization |