Faruq Akande

I am a detail-oriented bilingual professional (Yoruba-English) with proven expertise in translation evaluation, linguistic annotation, and data quality assurance. I specialize in analyzing AI-generated content for fluency, accuracy, and contextual meaning to support better machine translation outcomes.

My hands-on experience includes structured data labeling, annotation, and verification for ML-ready datasets using tools like Label Studio, Excel, and Appen and TELUS platforms. I have consistently delivered accurate student and project data, achieving 100% accuracy in several administrative and annotation tasks.

I have contributed to improved processes and engagement — including a documented 40% improvement in student engagement turnout — by developing structured annotation samples and facilitating data-driven process improvements. I am trained in prompt engineering and hold multiple AI- and professional-development certifications that strengthen my ability to optimize AI outputs.

I bring strong attention to detail, cultural sensitivity for Yoruba–English content, and reliable documentation and reporting practices. I seek roles where I can apply linguistic expertise and data-annotation skills to improve AI translation systems and ensure high-quality datasets.