Data Scientist | Mathematician | Problem Solver
Transforming complex data into actionable insights through innovative mathematical modeling and cutting-edge machine learning techniques
Hi! I'm Diana Kemunto, a passionate mathematician and data analyst with a love for creating innovative solutions to complex problems. My journey in the world of data science began with a fascination for patterns and a desire to solve real-world challenges through analytical thinking.
With expertise in machine learning, statistical analysis, and mathematical modeling, I specialize in developing solutions that bridge mathematical theory with practical applications. My work spans across various domains including financial analytics, predictive modeling, and operations research.
Completed my Bachelor’s Degree in Mathematics and Modelling Process at Dedan Kimathi University of University of Technology, I've gained practical experience through freelance data analysis work, quality control roles, and volunteer teaching positions. I believe in the power of collaboration and continuous learning to push the boundaries of what's possible in data science.
Class: Second upper. Specialized in computational mathematics and data analytics with focus on mathematical modeling and statistical analysis.
October 2021 - December 2024
Completed secondary education with strong foundation in mathematics and sciences.
December 2019
Gained practical experience in web scraping to extract company insights and predicted customer buying behavior using data science techniques.
Completed: August 6, 2023
October 2015
Machine Learning Models Comparison
Conducted an in-depth analysis to predict house prices using Decision Tree and Random Forest models. Evaluated performance using RMSE and R2 metrics, with Random Forest outperforming Decision Tree. Focused on hyperparameter tuning using Grid Search for optimization.
Financial Transaction Analysis
Conducted a fraud detection project to identify suspicious financial transactions using classification models. Trained and compared Logistic Regression, Decision Tree, and Random Forest models. Random Forest achieved the best results in identifying fraud cases.
Customer Behavior Prediction
Feel free to reach out! I'm always excited to collaborate on interesting projects, discuss new opportunities, or simply connect with fellow data science enthusiasts. Whether you have a project in mind or just want to chat about the latest in AI and machine learning, I'd love to hear from you!
Completed: August 6, 2023
Gained practical experience in web scraping to extract company insights and predicted customer buying behavior using data science techniques.
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