Data Analysis | Business intelligence Analyst Ifenna Daniel
My name is Ifenna, and I am a business intelligence and data analyst. My goal is to help individuals and companies scale in their endeavors by using data to derive deep insight into a particular problem or question. The realization of my goal lies in my expertise in Machine learning, statistical analysis, predictive modeling, and data visualization. I am a certified data analyst with certification from both the IBM professional course and the National Institute of Information Technology (NIIT) Abuja.
I enjoy working with data.
What's included
Bank Customer Churn Analysis
The object of the project is to identify which customers are likely to leave the bank and identify key drivers of churn to support retention strategies.
Process: I made use of R, Decision Tree, and Regression Tree, and performed EDA.
Data Cleaning: Removed duplicates, handled missing values
Feature Engineering: Encoded categorical variables, normalized features
Modeling: Trained multiple models — XGBoost achieved the best performance
Evaluation:
Accuracy: 86%
AUC Score: 0.89
Precision-Recall optimized for business impact
Starting at$25 /hr
Tags
Microsoft Excel
MySQL
R
Tableau
Data Analyst
Data Modelling Analyst
Data Scientist
Service provided by
Ifenna Daniel Nasarawa, Nigeria
Data Analysis | Business intelligence Analyst Ifenna Daniel
Starting at$25 /hr
Tags
Microsoft Excel
MySQL
R
Tableau
Data Analyst
Data Modelling Analyst
Data Scientist
My name is Ifenna, and I am a business intelligence and data analyst. My goal is to help individuals and companies scale in their endeavors by using data to derive deep insight into a particular problem or question. The realization of my goal lies in my expertise in Machine learning, statistical analysis, predictive modeling, and data visualization. I am a certified data analyst with certification from both the IBM professional course and the National Institute of Information Technology (NIIT) Abuja.
I enjoy working with data.
What's included
Bank Customer Churn Analysis
The object of the project is to identify which customers are likely to leave the bank and identify key drivers of churn to support retention strategies.
Process: I made use of R, Decision Tree, and Regression Tree, and performed EDA.
Data Cleaning: Removed duplicates, handled missing values
Feature Engineering: Encoded categorical variables, normalized features
Modeling: Trained multiple models — XGBoost achieved the best performance
Evaluation:
Accuracy: 86%
AUC Score: 0.89
Precision-Recall optimized for business impact
$25 /hr