// Data Scientist & ML Engineer
MS Data Science @ University at Buffalo. I build end-to-end ML systems, intelligent analytics pipelines, and data-driven products — from raw data to deployed models.
// 01 — work history
// 02 — selected work
Complete ML system from data ingestion to cloud deployment. Ran 16 classification experiments tracked via MLflow/DagsHub, served best model via FastAPI + Streamlit, fully Dockerized and deployed on Render.
View on GitHub →Scalable pipeline aligning 600K+ financial news headlines with 7,000+ U.S. stocks. Extracted sentiment via TextBlob & FinBERT, engineered temporal features, applied SHAP explainability across XGBoost and LSTM models.
View on GitHub →Led a 4-member team building a bilingual AI conversational agent for e-learning. Integrated OpenAI Whisper (STT), Meta AI NLP models for dialogue, and ElevenLabs TTS — with real-time low-latency processing.
View on GitHub →Intelligent classification system predicting epileptic seizures from 150×1,025 high-dimensional EEG data. Applied dimensionality reduction, normalization, and tuned SVM/RF/Logistic Regression — achieving 78% accuracy.
View on GitHub →End-to-end NLP pipeline scraping comments via YouTube Data API, applying VADER sentiment polarity detection and NRC Emotion Lexicon tagging. Visualized emotion distributions across millions of comments.
View on GitHub →Interactive Tableau dashboard analyzing national election results via Dawn API. Visualized voter turnout, candidate performance, regional vote share, and demographic breakdowns across all districts.
View Dashboard →// 03 — toolkit
// 04 — get in touch
I'm actively looking for Data Science, Data Analysis, and Business Intelligence internships. If you have an opportunity or just want to talk data — reach out.
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