Clovis Cheo

As a data science graduate from HAMK University of Applied Sciences in Finland, I have a strong interest in using data to solve real-world problems. My background combines technical skills in Python, machine learning, data analysis, and visualization with a practical, business-oriented mindset. I work with data across the full lifecycle, from cleaning and exploration to modeling, evaluation, and clear communication of results. I have hands-on experience using Python, SQL, Azure Machine Learning, and Tableau to build models, analyze patterns, and present insights in a way that supports better decision-making. What drives me is the process of turning complex or messy data into something meaningful and useful. I enjoy asking the right questions, testing ideas, and refining solutions until they deliver clear value. I am especially motivated by projects where data can improve efficiency, support smarter decisions, or create a positive impact. Designed and implemented end to end data science projects involving data cleaning, feature engineering, modeling, and evaluation using Python and SQL. Built and evaluated machine learning models including classification, regression, SVMs, and deep learning models, applying proper validation and performance metrics. Used Azure Machine Learning for model training, experiment tracking, and pipeline execution in cloud environments. Developed clear visualizations and dashboards using Tableau and Python libraries to communicate insights to technical and non technical audiences. Worked with real world datasets across domains including image recognition, sensor data, financial validation, and environmental monitoring. Applied machine learning and automation techniques to improve document processing accuracy, reliability, and scalability. I am currently seeking a data science role where I can continue learning, contribute to real projects, and grow alongside an experienced team.