Christopher N.

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STATISTICS

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Freelancer Overview

While I have not held a formal AI training or data labeling role, my academic and professional background has equipped me with directly transferable skills. Through my Data Science Diploma at WorldQuant University and my Quantitative Data Analysis certification from SONEK Data School, I have developed strong competencies in data handling, annotation logic, and quality assessment all of which are foundational to effective data labeling work. My final-year research project, a SARIMA time series analysis of youth mortality in Nyeri County using KNBS data, required rigorous data cleaning, validation, and structured documentation of analytical decisions, which closely mirrors the precision and consistency demanded in AI training workflows. During my industrial attachment at Nyeri County Government's Performance and Contract Unit, I worked extensively with structured datasets — organizing, interpreting, and ensuring data integrity across reporting pipelines. I also have hands-on experience with statistical and machine learning concepts, including classification models (Naïve Bayes), pattern recognition (Apriori algorithm), and model evaluation techniques. These experiences have sharpened my ability to apply systematic judgment when categorizing and reviewing data a core skill in AI training and labeling tasks. I am eager to bring this analytical mindset and attention to detail to a dedicated AI data role

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