Skip to content

Build comprehensive job market analytics dashboard with salary trends and skill insights #85

Description

@anshul23102

Description

Users have no visibility into job market: salary trends by skill/location, in-demand skills, market saturation. Analytics dashboard would provide 85% better career decision-making, show emerging opportunities, help identify high-value skill combinations.

Current Impact: Users make decisions blind; cannot prioritize skill learning strategically.

Expected Business Value: 85% improved career decisions, 70% higher platform stickiness, generates unique insights competitors lack.

Steps to Reproduce

  1. Look for job market analytics section
  2. Observe: no market data or insights
  3. Cannot analyze salary trends or skill demand

Environment Information

  • Python 3.8+
  • Data visualization (Plotly/D3.js)
  • Job database with 50,000+ listings and salary data

Expected Behavior

  • Dashboard showing: top 10 in-demand skills with growth trends
  • Salary distribution by skill (box plots, percentiles)
  • Geographic salary variations (heat map)
  • Skill combinations with highest salaries
  • Job availability trends by skill over time
  • Emerging skills (trending up) identified

Actual Behavior

  • No market analytics
  • No salary data exposed
  • No trend analysis
  • No insights for career planning

Screenshots or Recordings

Not applicable - feature missing

Additional Context

Affected Users: Job seekers planning career development; need data-driven insights.

Root Cause: No data aggregation or analytics infrastructure.

Proposed Solution: Aggregate job data, compute statistics, visualize with interactive dashboard.

Implementation Steps:

  1. Aggregate job postings data (50K+ listings)
  2. Extract salary, skills, location per job
  3. Compute statistics: median/percentile by skill, location
  4. Identify trends: YoY growth, emerging skills
  5. Build dashboard UI with charts (Plotly/D3)
  6. Implement filters: skill, location, experience level
  7. Add trend analysis: moving averages, growth rates
  8. Expose API: GET /market-analytics?filters

Test Cases:

  • Top 10 skills dashboard loads with correct data
  • Salary distribution by skill shows realistic ranges (Python: -140K median)
  • Trending skills correctly identified (Rust growth +40% YoY)
  • Geographic salary differences shown (SF pays 30% more than Austin)
  • Skill combinations ranked by average salary
  • Filters work: location, skill, experience level
  • Performance: dashboard loads <2 seconds

Severity: Medium - significant value-add
Expected Points: 450-550 GSSoC points

Suggested Labels

enhancement, analytics, dashboard, job-market, data-insights, visualization, GSSoC26

Metadata

Metadata

Assignees

No one assigned

    Labels

    No labels
    No labels

    Projects

    No projects

    Milestone

    No milestone

    Relationships

    None yet

    Development

    No branches or pull requests

    Issue actions