Actively building projects in machine learning, AI, and predictive analytics — with a growing focus on applying data to finance, trading, and investment decisions.
At a glance
Tech stack
01 — About
I'm an analyst actively building projects in Data Science, ML, and AI — with a strong interest in applying data to finance, trading, and investment decisions. My work spans healthcare ML, demand forecasting, and recommendation systems.
I enjoy the full pipeline: from raw data exploration and preprocessing to model building, evaluation, and communicating results clearly. Every project sharpens both technical depth and analytical thinking.
Currently expanding toward quantitative finance — exploring how ML models can decode market patterns and support smarter investment decisions.
02 — Projects
ML-based early detection system for CKD using patient clinical data. Trained and compared multiple classifiers — Random Forest delivered best-in-class results. Key predictors: serum creatinine, hemoglobin, blood pressure, and albumin.
Time-series demand forecasting for NYC taxi trips to enable smarter fleet allocation and route optimization across boroughs.
Collaborative filtering system generating personalized suggestions based on user behavior patterns and item similarity.
Regression model predicting salary ranges from job-related features — useful for HR analytics and compensation benchmarking.
03 — Skills
Languages & Environments
ML & Data
Visualization & Tools
04 — Contact
Open to collaborations, internships, and opportunities in Data Science, ML, and FinTech. Always happy to talk data, projects, or the intersection of AI and finance.