Junior data scientist with a full-stack development background, currently building practical ML projects from the ground up. Over the past few months I’ve worked hands-on across the full data science stack: Python, NumPy, pandas, data preparation and cleaning, supervised learning (KNN, logistic regression, SVM, LDA), time series (ARIMA, SARIMA), deep learning (autoencoders), and scikit-learn pipeline design. I’ve also explored AI agents and small language model prompting.
As a final bootcamp project, I led rec_o: a music recommendation system with a self-hosted MusicBrainz PostgreSQL database on Google Cloud, a FastAPI backend with KNN models, ListenBrainz and ntfy integrations, and a Next.js frontend deployed on Vercel. I owned the project end-to-end, from infrastructure to delivery and presentation.
I’m looking for junior data roles where I can keep learning by shipping real things alongside an experienced team.
