Employment and Wage Analysis in AzureML

This comprehensive wage analysis solution examines employee compensation across the United States using advanced regression techniques in Azure Machine Learning. By analyzing factors such as industry, geographic location, and state-specific variables, we provide critical insights into wage determinants and patterns.

KEY INSIGHTS

Data Analysis

  • Analyzed 6.4+ million wage records from the US Bureau of Labor Statistics

  • Identified geographic and industry-specific wage variations

  • Revealed critical connections between location, industry, and compensation

Feature Importance

  • Geographic Factors: Location significantly impacts wage levels across industries

  • Industry Classification: Different sectors show distinct compensation patterns

  • Temporal Trends: Year-over-year wage progression reveals economic patterns

Model Performance

  • Implemented multiple regression models with comprehensive performance metrics

  • Utilized variance analysis, MAE, RMSE, and R2 score for model evaluation

  • Applied advanced feature engineering for improved prediction accuracy

Business Applications

  • Labor Market Intelligence: Regional compensation insights for competitive analysis

  • Strategic Planning: Data-driven location selection for business operations

  • Compensation Strategy: Industry-specific benchmarking for talent acquisition

  • Economic Analysis: Trends and patterns for market entry decisions

Technologies Leveraged

  • Azure Machine Learning, Python, LightGBM, Tree-Based Models, Pandas, Scikit-learn

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