Victor Olaogun

I’m a results-driven Data Analyst with a strong foundation in Python, SQL, Power BI, and Excel, plus 2+ years of hands-on experience in AI data annotation, data quality assurance, and business intelligence. I focus on clean data pipelines, accurate modelling, and building data products that drive measurable business outcomes.

In my current Data Analyst Intern role, I analyze customer behavior and product usage datasets to identify trends and support strategic decisions. I design and deploy interactive Power BI dashboards for KPI monitoring, and I engineer Python scripts for automated data cleaning and weekly report generation—saving 5+ hours per week. I also write optimized SQL queries to extract, manipulate, and validate large datasets, and I use Excel and SQL to analyze A/B testing results for feature rollout evaluation.

As an AI Annotation Specialist, I structured and labeled 15,000+ medical images for a health AI model, achieving 98% annotation accuracy and improving training performance. I validate and quality-assure large-scale multimodal datasets (image, video, text, audio), including transcribing and annotating 200+ hours of audio for voice recognition, while conducting peer review and guiding new annotators. I operate across tools like CVAT, Label Studio, LabelImg, SuperAnnotate, and DataCompute to maintain consistent, ethically labeled training data.