Job Title: Python Developer for Geophysical Data Analysis (K-Means Clustering & 3D Visualization) Project Overview: I am a Geophysics student working on a structural mapping project of the Red Sea Rift. I have a dataset of 50 years of earthquake records (USGS CSV format) and need a Python expert to build a machine learning workflow that clusters these events based on their seismic attributes to identify hidden fault structures. Scope of Work: Data Pre-processing: Clean a USGS earthquake catalog and perform feature scaling on four specific attributes: Latitude, Longitude, Depth, and Magnitude. Unsupervised Machine Learning: * Implement K-Means Clustering to group seismic events. Provide an Elbow Method plot to justify the optimal number of clusters (K). 3D Visualization: * Create an interactive 3D Scatter Plot (using Plotly or similar) where earthquakes are plotted by Lat/Long/Depth. Color-code the points by their AI-assigned Cluster ID and size them by Magnitude. Geophysical Statistics: Create a function to calculate the b-value (Gutenberg-Richter Law) for the identified clusters. Deliverables: A clean, commented Jupyter Notebook or Python script that I can run on my Mac. Technical Requirements: Expertise in Scikit-Learn (K-Means, StandardScaler). Experience with Pandas and Plotly/Matplotlib. Background in Geophysics or Earth Sciences is a huge plus, but not required if you are strong in spatial data clustering.