emmanuel rono

Provide STEM tutoring via AI-assisted platforms, review and refine AI-generated content for accuracy and clarity, and collaborate on workflows and content guidelines to improve learner engagement.

Annotated and QAed over 500,000 conversational datasets for LLM training, designed and refined annotation guidelines achieving 98% accuracy, and improved annotation workflows by 40% through process optimization and team training.

Developed Python and SQL data pipelines for real-time analytics, optimized database schemas and queries to reduce data retrieval times by 30%, and conducted data audits to ensure ML dataset integrity.

Designed Python automation scripts to streamline annotation processes reducing task time by 35%, used SQL to query large datasets and improve client reporting accuracy by 20%, and created scalable data workflows for ML models.

Managed multilingual conversational annotation projects, conducted prompt engineering to improve AI responses across domains, and mentored a team of 10 specialists to deliver high-quality datasets.

Curated and annotated datasets for customer service automation projects achieving 98% accuracy, delivered insights and reports on annotation outcomes, and contributed to continuous process improvements.

Annotated image and text datasets for retail and e-commerce AI models and contributed to taxonomy development for large-scale product data categorization.

Bachelor of Science in Computer Science with focus on Data Management, Computational Linguistics, and Artificial Intelligence completed between August 2010 and May 2014.