Mher M.

Key Skills

Freelancer Overview

I have experience working with data annotation and AI training data projects that involve preparing, labeling, reviewing, and validating datasets used to train machine learning models. My work has included organizing structured and unstructured data, performing quality assurance checks, identifying labeling inconsistencies, and following detailed annotation guidelines to ensure high-quality outputs. I am comfortable working with large datasets and maintaining accuracy while meeting productivity targets. In addition to data labeling, I have a strong foundation in data science, statistics, Python, SQL, and machine learning concepts, which helps me better understand how training data affects model performance and why consistency and precision are critical throughout the annotation process. What sets me apart is my combination of technical knowledge and analytical thinking. I have academic and practical experience in machine learning, including clustering algorithms such as K-Means, DBSCAN, and Hierarchical Clustering, as well as data preprocessing, feature analysis, and model evaluation. I am highly detail-oriented, capable of identifying edge cases, and committed to maintaining data quality standards. My background in data science allows me to understand not only how to label data correctly but also how that data will ultimately be used to improve AI systems. I am a fast learner, adapt quickly to new guidelines and tools, and work effectively both independently and as part of a distributed team. These skills enable me to contribute reliable, accurate, and scalable training data that supports the development of high-performing AI models.

Education

Work History