I am an adaptable and results-driven Data Scientist and MLOps Engineer with a strong foundation in designing and deploying scalable AI systems. My expertise spans the full machine learning lifecycle; from data engineering and feature development to training, deployment, and observability. Ensuring that models not only deliver accurate insights but also integrate seamlessly into production environments.

I have partnered with researchers, engineers, and cross-functional teams to deliver high-impact projects, from real-time job-matching platforms powered by embedding-based modeling to ETL workflows processing hundreds of millions of healthcare records. My philosophy centers on scalability and impact by leveraging cloud platforms, modern MLOps practices, and statistical rigor to deliver solutions that create measurable outcomes and lasting value.