Welcome to My Portfolio
My Name Is Ridwan Shittu
Data Scientist | GIS Enthusiast
Data Scientist | GIS Enthusiast
Hello, I'm Ridwan Shittu, a passionate Researcher, Data Scientist and GIS Enthusiast with a strong background in data pre-processing, data visualisation and applications of statistical/machine learning algorithms. I'm dedicated to leveraging data to gain insights and create impactful visualizations.
With Python, R, QGIS, and ArcGIS Pro expertise, I've successfully executed various projects involving data science and analytics and Geographical information system approaches across diverse research domains; see the portfolio section and tutorial for more. I aim to continue pushing the boundaries of data and GIS analyses to solve real-world problems.
Description: This project aimed to leverage advanced data analysis techniques to optimize crop yield, resource management, and sustainability in an agricultural setting. By analyzing a comprehensive dataset encompassing crop details, weather indices, irrigation practices, and more, the project sought to extract insights for informed decision-making and improved agricultural practices.
Skills Used: Data Preprocessing, Exploratory Data Analysis, Predictive Modeling, Geospatial Analysis, Visualization, Statistical Analysis, R Programming
Impact: Through the application of advanced data analysis techniques, the project provided valuable insights into various aspects of agricultural operations
Description: This project aimed to uncover customer churn patterns within an insurance company using an extensive dataset. Applying advanced data analysis techniques, the project sought to identify factors contributing to policyholder churn, enabling the insurance company to develop targeted retention strategies and enhance customer satisfaction.
Skills Used: Data Preprocessing, Exploratory Data Analysis, Predictive Modeling, Customer Segmentation, Visualization, Statistical Analysis, R Programming
Impact: The project yielded valuable insights into customer churn patterns, leading to meaningful outcomes
Description: This project focused on unraveling customer behavior patterns and assessing the performance of different supermarket branches using a comprehensive transactional dataset. By applying advanced data analysis techniques, the project aimed to gain insights into customer preferences, loyalty, and branch-specific trends, ultimately driving informed business strategies and operational enhancements.
Skills Used: Data Cleaning, Exploratory Data Analysis, Customer Segmentation, Time-Series Analysis, Visualization, Statistical Analysis, R Programming
Impact: The project's data analysis efforts led to valuable insights and actionable outcomes
You can also connect with me on LinkedIn.