I build things that look good and think.
2+ years freelancing in visual design (15+ client projects) — now going deep on Data Science, Machine Learning, and GenAI.
My focus: where design intuition meets data-driven products.

• Listener-Segmentation — Unsupervised K-Means clustering on music listening behavior (hours/week, songs/day, skip rate, playlist count) to segment users into Casual Listener, Music Explorer, and Heavy Listener profiles. Built in Streamlit; a parallel Google AI Studio/Antigravity build explores a more dynamic, illustrated UI.
• AI Brand Studio — A generative AI branding assistant that produces logo concepts, color palettes, fonts, social posts, captions, and brand guidelines via LLM + image-gen APIs. Design background meets applied GenAI.
• Customer Intelligence & Sales Forecasting Platform — Customer segmentation (K-Means), churn prediction (Logistic Regression / Random Forest), and sales forecasting (ARIMA), SQL-backed with a Streamlit dashboard.
• Global Billing Platform (early planning) — Invoicing/billing SaaS designed to work for businesses in any country, following local tax/regulatory rules.

LSTM/RNN · VAE · ensemble methods (Bagging/Boosting/Stacking) · production Streamlit deployment

Preparing for a Pre-Placement Assessment (Data Science, AI/GenAI, Full Stack, Cloud, IoT, Embedded Systems) — and building a portfolio that shows design + ML work side by side, not as two separate people.

LinkedIn · Open to internships/roles at the intersection of design and applied ML

Design intuition. Data discipline. One person, one skillset.