I am an aspiring AI/ML engineer with hands-on experience in machine learning, predictive modeling, data analysis, and dashboard development. I enjoy transforming raw data into practical insights and decision-support solutions.
I work with Python and SQL for data cleaning, analysis, and model development. My technical foundation includes machine learning workflows, preprocessing, feature engineering, validation, and performance evaluation.
I have built predictive models using Scikit-learn, including a surgical complication risk model that achieved strong accuracy, ROC-AUC, recall, and precision metrics. I am particularly interested in applied AI for healthcare and predictive analytics.
I also have end-to-end analytics experience using Excel, SQL, Python, Power BI, and Tableau. I can validate datasets across multiple tools, identify meaningful trends through correlation analysis, and communicate findings through interactive dashboards and KPI reporting.
I am seeking an entry-level Machine Learning or Data Science opportunity where I can apply my analytical thinking, curiosity, and fast learning ability. I am eager to grow my expertise in deep learning, computer vision, natural language processing, and applied AI.
