Data Scientist. Applied ML Systems Builder.

I'm a Data Scientist building production-grade ML systems across fraud scoring, forecasting, segmentation, and real-time APIs. Currently at ZeitstoneAI, where I work on weighted fraud-risk scoring pipelines and take models from data and experimentation toward real-world deployment.

My work spans supervised and unsupervised ML, statistical experimentation, and ML engineering, with hands-on experience across CatBoost, XGBoost, KMeans, FastAPI, Docker, AWS, and MLflow.

Beyond traditional ML, I also build with LLMs, RAG, fine-tuning, and AI applications, exploring how intelligent systems can be made useful, reliable, and practical.

I freelance on the side, working on automation and analytics projects that turn repetitive workflows and messy data into systems people can actually use. Outside of all that, I'm a chess player, reader, and builder who enjoys side projects, experiments, and occasionally going far too deep into something just because it caught my curiosity.