Mark Mosoti
Machine Learning Data Annotator- Mathematics @DataAnnotation
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WORK HISTORY
Machine Learning Data Annotator- Mathematics @DataAnnotation
US
Evaluated 400+ complex mathematical problems across algebra, calculus, statistics, and advanced mathematics to train large language models, contributing directly to AI model accuracy improvements.• Maintained 95%+ quality score consistently across mathematical reasoning tasks, ranking among top-tier annotators for precision and adherence to evaluation standards.• Identified and documented critical reasoning errors in AI-generated solutions, providing detailed feedback that directly improved model performance through RLHF (Reinforcement Learning from Human Feedback) processes• Assessed mathematical problem difficulty across 5+ complexity tiers, enabling proper dataset curation and targeted model training for varying skill levels.• Demonstrated expert-level proficiency in evaluating AI mathematical reasoning across multiple advanced domains including linear algebra, differential equations, probability theory, and discrete mathematics.• Delivered high-volume output of 50 expert mathematical evaluations weekly while maintaining exceptional accuracy standards and meeting strict project deadlines.
EDUCATION
The University of Texas at Dallas
MS in Business Analytics and Artificial Intelligence
Kenya Institute of Management
Diploma in Purchasing and supplies Management
University of Nairobi
Bachelor of Arts (B.A.), Economics and Mathematics
University of Nairobi
Master of Arts (M.A.), Economics
ABOUT MARK MOSOTI
Results-driven and data-savvy Supply Chain professional with over 10 years of progressive experience in inventory management, procurement analytics, retail operations, and logistics. I specialize in leveraging data science, artificial intelligence, and machine learning to drive business intelligence, streamline operations, and optimize decision-making across supply chain functions.With a strong command of Power BI, SQL, Python, and ERP/CRM systems, I\'ve led cross-functional teams, engineered predictive models, and developed advanced dashboards that have significantly improved reporting accuracy, reduced operational costs, and enhanced customer satisfaction. My experience spans end-to-end supply chain operations—from inventory control and order fulfillment to data visualization and strategic planning.Over the past year, I\'ve expanded my AI expertise through hands-on machine learning data annotation, evaluating 400+ complex mathematical problems for large language model training with 95%+ quality scores. This work has deepened my understanding of RLHF (Reinforcement Learning from Human Feedback) processes and AI model evaluation, allowing me to bridge traditional supply chain analytics with next-generation AI applications.Currently pursuing a Master of Science in Business Analytics and Artificial Intelligence at the University of Texas at Dallas, I am passionate about integrating cutting-edge technology into supply chain ecosystems to deliver sustainable and measurable results.
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