Skip to content
View JayDataWorld08's full-sized avatar
🎯
Focusing
🎯
Focusing

Block or report JayDataWorld08

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Please don't include any personal information such as legal names or email addresses. Maximum 100 characters, markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
JayDataWorld08/README.md

👋 Hey there, I’m Jayesh

🎓 Master’s in Analytics @ Northeastern University (2024–2026) — GPA 4.0
📍 Boston, MA | 📧 [email protected] | 🔗 LinkedIn


🚀 About Me

I’m a data-driven problem solver who blends analytics, machine learning, and strategic thinking to turn raw data into actionable insights.
With roots in Operations & Supply Chain Management and hands-on experience across logistics, marketing, and predictive analytics, I thrive where numbers meet impact.

💡 I love:

  • Finding hidden patterns in messy data
  • Designing machine learning models that actually get deployed
  • Making decisions backed by data, logic, and a little curiosity

🛠 Tech & Tools

Languages: Python, R, SQL, MATLAB
Analytics & ML: Scikit-learn, TensorFlow, CatBoost, LightGBM, PCA, KMeans
Visualization: Tableau, Power BI, Matplotlib, Seaborn
Databases: MySQL, PostgreSQL, SQL Server
Other: Excel (Advanced), Data Wrangling, Statistical Modeling


📂 Highlight Projects

🛣 Traffic Crash Analysis (ML)

  • Predicted injury severity with 94% accuracy using CatBoost & LightGBM
  • Identified crash archetypes via K-means & PCA
  • Applied Apriori rule mining for risk factor patterns

🚔 Traffic Stop Disparities – NC State Patrol EDA

  • Logistic regression & chi-square analysis to reveal disparities in searches
  • Found correlation between demographics and search probability

🛡 Zero-Day Attack Detection (SQL)

  • Real-time anomaly detection system for airport logistics networks
  • Achieved 95% threat reduction through advanced SQL queries & monitoring

🌱 Zero Waste Retail Location Model

  • Ranked Massachusetts neighborhoods by “refill-readiness” score
  • Used clustering + Huff Model for market share estimation

🌍 Beyond the Code

  • Collaborator: I enjoy cross-disciplinary teamwork
  • Problem Solver: From optimizing shipping routes to forecasting demand
  • Impact-Driven: I use data for safer roads, greener cities, and smarter logistics

📬 Let’s Connect!

📧 Email: [email protected]
🔗 LinkedIn: linkedin.com/in/jayeshp-242e
💻 GitHub: github.com/JayDataWorld08


“Data without context is just noise — I turn it into music.”

Popular repositories Loading

  1. Attack-Detection-on-Logistics-Network Attack-Detection-on-Logistics-Network Public

    Database-driven Zero-Day Attack Detection for airport logistics using SQLite. Detects anomalies in real time, analyzes network traffic, and generates risk reports to help security, IT, and logistic…

  2. Exploratory-Data-Analysis-North-Carolina-State-Patrol-Traffic-Stops Exploratory-Data-Analysis-North-Carolina-State-Patrol-Traffic-Stops Public

    This project presents an Exploratory Data Analysis (EDA) of North Carolina State Patrol traffic stop data, sourced from the Stanford Open Policing Project. It examines demographic patterns, search …

    R

  3. Global-Energy-Trends-and-Nuclear-Analysis Global-Energy-Trends-and-Nuclear-Analysis Public

    Analysis of global energy production trends, focusing on nuclear energy’s role in sustainability, safety impacts, and fuel dependency shifts. Includes Tableau visualizations, insights on energy div…

  4. Energy-Consumption-Analysis Energy-Consumption-Analysis Public

    Predictive modeling and seasonal trend analysis of building energy usage using statistical methods, correlation studies, and time series forecasting to identify key drivers, seasonal impacts, and f…

    R

  5. Connecticut-Real-Estate-Insights Connecticut-Real-Estate-Insights Public

    Data-driven analysis of Connecticut real estate sales (2001–2022) using EDA and KMeans clustering to uncover market trends, value drivers, and anomalies, with an interactive dashboard for investors…

    Jupyter Notebook

  6. Traffic-Crash-Analysis-ML Traffic-Crash-Analysis-ML Public

    Machine learning–driven analysis of 195k+ traffic crash records using SVM, CatBoost, LightGBM, K-means, PCA, and Apriori rule mining to predict injury severity, identify crash archetypes, and recom…

    Jupyter Notebook