About Me
Data professional with a Post Graduate Diploma in Data Science & Analytics and a multidisciplinary academic background in Economics and Mathematics. Hands-on experience building data dashboards, applying machine learning…
Data professional with a Post Graduate Diploma in Data Science & Analytics and a multidisciplinary academic background in Economics and Mathematics. Hands-on experience building data dashboards, applying machine learning and deep learning models, and delivering analytics projects across SQL, Python, and Power BI. Strong analytical foundation from formal training in economics and statistics, paired with practical exposure to real-time AI pipelines and data visualization. Seeking to apply data analysis and machine learning skills to drive measurable business and operational insight.
Experience
Dashboard Developer Intern
Developed a web-based analytics dashboard using PHP CodeIgniter and MySQL to track and report on data from 9 university administrative services, including Bonafide, Condonation, and College Transfer requests. Built data visualization modules to monitor live application status (total, processing, pending, reopened) across services, improving application-tracking efficiency by 30%. Implemented multi-format data export (Excel, PDF, Print), cutting manual reporting time by 25% for administrative staff. Designed a responsive HTML/CSS front-end for cross-device access by students and university administrators.
AI/ML Trainee (Data Science Intern)
Built a real-time hand gesture recognition pipeline using OpenCV and a VGG16-based deep learning model, classifying American Sign Language gestures and converting them to speech output to support accessibility for hearing-impaired users. Designed and implemented a full feature-extraction-to-classification pipeline in Python, achieving 90%+ classification accuracy on the gesture dataset. Optimized the real-time inference pipeline to reduce processing latency by 20% and gesture misclassification rate by 20%, through preprocessing and pipeline tuning. Worked hands-on with Scikit-learn and hand-tracking modules for data preprocessing, model evaluation, and live-output integration.