One of the most impactful projects I worked on involved building a data-driven risk prediction system for a healthcare sector. We used Azure ML to train classification models, with Jupyter Notebooks for EDA and prototyping, and Power BI for stakeholder-facing dashboards.
I lead the model development pipeline, ensuring proper data preprocessing, and tuning hyperparameters for optimal performance. We also used Visual Studio Code with Git integration for collaboration and version control.
The project resulted in a fully deployed solution that helps medical professionals prioritize at-risk patients based on real-time inputs. It was rewarding to see how technology directly impacted decision-making in a critical domain.
I continue to explore tools like Claude AI to automate documentation and generate technical summaries faster, which enhances team productivity and allows more time to focus on core innovation.
