I am a dedicated Data Analyst with a strong foundation in Applied Science, specializing in data analytics and machine learning. Recently, I completed my internship as a Junior GIS Analyst, where I honed my skills in spatial data analysis, SQL, Python, R, and Power BI.
My passion lies in transforming complex datasets into meaningful insights to drive data-driven decision-making. I have worked on various projects, including predictive modeling, customer segmentation, and dashboard development using R, Python, and SQL. My GitHub showcases projects in data visualization, machine learning, and artificial intelligence.
I am actively seeking job opportunities where I can apply my analytical skills, collaborate with cross-functional teams, and continue growing as a data professional.
Let's connect! 🚀
| Programming Language | Proficiency |
|---|---|
| Python | ⭐⭐⭐⭐ |
| R | ⭐⭐⭐ |
| SQL | ⭐⭐⭐ |
| C | ⭐⭐ |
- Data Analysis: Data cleaning, preprocessing, modelling, and visualization
- Machine Learning: AI-based models, deep learning techniques
- GIS Analysis: Spatial data analysis and visualization
- Computer Vision and AI-Based Ripeness Classification of Oil Palm Fruits: Developed a model using Python and AI techniques, achieving a 98% accuracy rate in classifying the ripeness of oil palm fruits.
- Sales Data Analysis: Analyzed and visualized sales data using SQL and R, identifying key trends and insights to drive business decisions.
- Customer Segmentation: Implemented clustering techniques in Python to segment customers based on purchasing behaviour, enabling targeted marketing strategies.
I'm continuously expanding my data science and analytics knowledge through coursework, personal projects, and industry experience. I aim to become a proficient data scientist capable of solving real-world problems using data-driven approaches.
Feel free to explore my repositories to see some of the work I've been involved in!