PhD-trained Data Analyst with expertise in data analysis, machine learning, and business intelligence.
I have developed end-to-end data projects covering:
- Predictive modeling (churn prediction)
- Time series forecasting
- Customer segmentation
- Business intelligence dashboards
- Real-world business analysis (Café Harmony case study)
- Behavioral & Retention Analytics
- Machine Learning classification project
- Built using Python and logistic regression
- Identifies customers likely to churn
- Forecasted future sales using time series analysis
- Applied Exponential Smoothing
- Evaluated using MAE and RMSE
- Applied K-Means clustering
- Identified customer groups based on behavior
- Supports targeted marketing strategies
- Built interactive dashboard
- Shows revenue, product, and regional performance
- Includes KPIs and filters
- Business analytics project using Excel and Python
- Performed data cleaning, exploratory analysis, and visualization
- Identified sales trends, product performance, and operational insights
- Aggregated daily data into monthly trends for clearer business interpretation
- Conducted end-to-end analysis of sales and customer data to identify growth opportunities
- Segmented users and identified high-risk groups
- Uncovered weak alignment between performance and compensation
- Delivered business recommendations to improve retention and decision-making
- Python (Pandas, NumPy, scikit-learn)
- SQL
- Power BI
- Excel (Data Cleaning & Analysis)
- Data Visualization
- Machine Learning
- Time Series Analysis
- Data Storytelling
https://github.com/afeisede/customer-churn-prediction.git
https://github.com/afeisede/Sales-Forecasting.git
https://github.com/afeisede/customer-segmentation.git
https://github.com/afeisede/sales-dashboard.git
https://github.com/afeisede/cafe-harmony-business-analysis.git
https://github.com/afeisede/nextgen-employee-success-analytics-sql.git
Email: afeisede@gmail.com
GitHub: https://github.com/afeisede
LinkedIn: www.linkedin.com/in/hamzatafeisede