{"version":"1.0","type":"rich","title":"Untitled","description":"This interactive visualization explores the U.S. data science job market by comparing the semantic similarity of job descriptions and positions. It presents two t-SNE scatter plots—one for raw position titles and one for job descriptions—where each point represents a job posting, colored by job category (e.g., Data Analyst, Data Scientist). A confusion matrix shows classification accuracy from a bagging ensemble of linear SVM classifiers, with cell color intensity indicating the proportion of predictions. The React-based interface uses D3.js (`scaleLinear`, `scaleOrdinal`) for scales and rendering, with SVG circles. Hovering over a legend category highlights that class's points across all views and fades others (opacity 0.2), enabling cross-referencing of how descriptions map to titles. Data originates from a Kaggle dataset of 7,000 Indeed job postings.","provider_name":"VizHub AI Studio","provider_url":"https://vizhub.com","html":"<iframe src=\"https://vizhub.com/viz/a92093d1eeee4181beca70205cb9b53a?mode=embed\" width=\"960\" height=\"500\" scrolling=\"no\" frameborder=\"0\"></iframe>","width":960,"height":500,"cache_age":3600}