I’m a data scientist who enjoys digging into how businesses, processes, and operations really work, and turning that understanding into data-driven products that help people make better decisions. Over the years, I’ve worked in industry building and deploying end-to-end ML and analytics solutions in B2B and SaaS environments, from designing data pipelines and modeling workflows to putting forecasting, risk, and customer intelligence models into production. What I enjoy most is translating messy, complex systems into clear, reliable solutions that create real business impact and guide everyday decisions.
My background combines a strong academic foundation with proven industry experience, complemented by hands-on machine learning and statistical modeling applied to real-world business problems. This made me comfortable moving between strategic thinking and detailed implementation. I like working closely with product, engineering, and business teams, where data, domain knowledge, and curiosity come together to shape scalable and robust data workflows and decision-support systems.