Resume
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These are some recent data science and business analytics projects that demonstrate my technical capabilities and problem-solving skills across industries.
Built an intelligent product recommendation system that combines web scraping, semantic retrieval, and lightweight LLM generation.
Built a GNN-based disease hotspot prediction system using Spark and geospatial health-environment data for U.S. counties.
Designed a platform using Uber, Google Maps, and Weather APIs to analyze pricing, wait times, and route efficiency in the Bay Area.
Used logistic regression, clustering, and PCA to analyze self-collected data; identified tipping predictors like mileage and interaction.
Built XGBoost models (98.9% accuracy, 0.998 AUC) to predict churn and lifetime value, offering actionable segmentation insights.
Built a chatbot using Hugging Face Transformers with multi-turn context and ROUGE-optimized response ranking.
Applied ML techniques to identify reasons behind bank customer churn and provided actionable recommendations.
Executed a full pipeline for customer segmentation using K-Means and data storytelling for a retail company.
Transformed unstructured feedback into actionable recommendations using sentiment analysis techniques.
Focus on the core technology stack and professional skills assessment in the fields of data science and business analysis.
MySQL, PostgreSQL, MongoDB
Tableau, Power BI, Matplotlib, Sigma, Looker
AWS, Azure, Google Cloud, Oracle
Git, Docker, Jupyter
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