Federal University of Technology, Akure
Bachelor of Technology, Meteorology
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I have experience working at the intersection of data analysis, environmental science, and AI-focused research, where I’ve handled large datasets that required strong attention to detail, accuracy, and structured labeling processes. Through my work with the Nigerian Meteorological Agency and Climate Change AI, I worked extensively with weather and climate datasets—cleaning raw data, identifying inconsistencies, organizing structured datasets, and ensuring data quality for analysis and modeling. This involved tasks similar to data labeling, such as categorizing environmental variables, validating datasets, and preparing high-quality inputs for machine learning and research applications. I’m also highly proficient in SQL, Excel, and Power BI, which allows me to efficiently manage large datasets and maintain accuracy at scale. What sets me apart is my analytical mindset combined with precision and adaptability. I’ve built real-world datasets from scratch, cleaned complex multi-table datasets, and worked on projects involving pattern detection, quality assurance, and business insights. My background in Meteorology and Climate Science has trained me to work with highly sensitive datasets where small errors can significantly impact outcomes. I’m a fast learner, comfortable working with repetitive but detail-oriented tasks, and I understand the importance of producing reliable training data that improves AI model performance.
Bachelor of Technology, Meteorology
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