About

This canvas performs comprehensive exploratory data analysis and predictive modeling on a global data science salaries dataset (607 records), comparing linear regression and gradient boosting models via 5-fold cross-validation with fold-safe target encoding on job titles. The workflow generates salary summaries by experience level, remote ratio, company size, and year; produces styled visualizations of trends and correlations; builds and benchmarks predictive models achieving ~22% R² with fold-averaged RMSE of ~$62K; and synthesizes actionable insights for job seekers and employers, finding that job title and experience level drive 76% of salary variance, fully remote roles command a $16K premium, and the market grew 30% from 2020–2022.