💡 Passionate about leveraging Data Science, Machine Learning, and NLP to solve real-world problems.
🎓 Pursuing Ph.D. in Data Science & Engineering at the University of Tennessee, Knoxville (UTK).
🔬 Former Research Associate at the Research Foundation of CUNY (RF CUNY), working on affordable housing, climate change, environmental justice, and extreme heat research in New York City.
🔍 Interested in Big Data, AI Ethics, Climate Analytics, and Healthcare Analytics.
🚀 Open to collaborations, research opportunities, and internships in Data Science & AI.
📍 Based in Knoxville, TN | Open to Relocation

• Conducted data-driven research on affordable housing, climate change, environmental justice, and extreme heat in New York City.
• Analyzed socioeconomic, environmental, housing, and geospatial datasets to study heat vulnerability and climate resilience.
• Applied machine learning, statistical analysis, and data visualization to identify patterns and relationships in large-scale datasets.
• Developed analytical workflows and geospatial visualizations to support research on urban heat exposure and vulnerable communities.
• Contributed to interdisciplinary research connecting data science, climate resilience, affordable housing, and environmental justice.

Tech Stack: Python, Pandas, NumPy, Scikit-learn, XGBoost, SHAP, Geospatial Analysis, Matplotlib, Seaborn

• Programming: Python, R, SQL, NoSQL, C, C++, JavaScript
• Machine Learning: TensorFlow, PyTorch, Scikit-learn, Hugging Face Transformers
• Big Data: Apache Spark, PySpark, Hadoop, Databricks, HDFS, Hive
• NLP: NLTK, spaCy
• Databases: MySQL, PostgreSQL, Firestore, MongoDB
• Cloud Platforms: Google Cloud (Firestore, Firebase Admin SDK)
• Data Visualization: Tableau, Power BI, Matplotlib, Seaborn
• Web Scraping & Automation: Flask, BeautifulSoup, Selenium

Machine Learning & Geospatial Analysis on NYC Heat Vulnerability & Affordable Housing
🔹 Processed 55,000+ data entries to develop geospatial visualizations.
🔹 Built an XGBoost model (R² = 0.99, RMSE = 0.033) for predictive analysis.
🔹 Tech Stack: Python, SHAP, XGBoost, Random Forest, Geospatial Visualization

Real-time NLP-based Fake News Detection System
🔹 Built an NLP pipeline using Transformers and custom word embeddings.
🔹 Achieved 96% accuracy using Scikit-learn, SHAP & LIME for model explainability.
🔹 Tech Stack: Python, NLP, Transformers, SHAP, LIME

🔹 Developed a secure real-time networking platform for programmers & cybersecurity professionals.
🔹 Integrated Firebase Authentication for user authentication & structured Firestore for data storage.
🔹 Tech Stack: Google Cloud, Firebase, Firestore, Python

Automated Web Scraper with an Interactive GUI
🔹 Scraped search engine results using BeautifulSoup & Selenium.
🔹 Built an interactive Flask-based GUI to rank search results by frequency analysis.
🔹 Tech Stack: Python, Flask, BeautifulSoup, Selenium, OCR

💼 LinkedIn: linkedin.com/in/mahbuba-datascience
🔗 GitHub: github.com/mahbuba-datascience
📧 Primary Email: mahbuba.jyoti2022@gmail.com