Imeobong Monday
Data Analyst | Excel, Power BI, SQL, Python | Dashboards.
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Built a credit scoring model to predict customer default risk and support lending decisions.
This project focuses on turning raw financial data into a reliable risk assessment system.
What I built:
• Data cleaning and preprocessing for financial datasets
• Feature engineering to capture customer risk behavior
• Classification model to predict likelihood of default
• Model evaluation to ensure accuracy and reliability
How it works:
Customer data → Cleaning → Feature engineering → Model training → Risk prediction
Key value:
• Identifies high-risk customers before issuing credit
• Supports smarter lending decisions
• Reduces potential financial losses
• Improves risk management strategy
Use cases:
• Loan approval systems
• Credit risk assessment
• Financial decision support
Tools:
Python | Pandas | scikit-learn | NumPy | Jupyter Notebook
Outcome:
• Predictive model for default risk
• Structured workflow for financial data analysis
• Business-ready insights for credit evaluation
If you need a data-driven solution for risk analysis or predictive modeling, let’s work.
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Built a retail analytics system focused on customer churn and business insights.
This project is not just a dashboard. It combines data processing, analysis, and business interpretation into one system.
What this project does:
• Analyzes retail transaction data
• Identifies patterns behind customer churn
• Highlights key drivers affecting retention
• Transforms raw data into decision-ready insights
System flow:
Raw data → Cleaning & transformation → Analysis → Insight generation → Dashboard
Key focus:
• Understanding why customers stop buying
• Turning data into actionable business insights
• Structuring data for reliable analysis
• Supporting retention strategy decisions
What this solves:
Customer churn directly impacts revenue.
This system helps:
• Identify at-risk customers
• Understand behavior patterns
• Support targeted retention strategies
Tools used:
Python | Pandas | SQL | Excel / Power BI
Outcome:
• Clear visibility into customer behavior
• Insight-driven approach to retention
• Structured analytics system for retail data
This is part of a larger goal to build full data systems that connect engineering, analytics, and business impact.
If you need data turned into real business insight, let’s work.
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