@vantigo/career-score

Multi-dimensional career health scoring algorithm. Combines salary percentile, AI automation resilience, market timing, and demand signals into a single interpretable Career Score (0–100).

Installation

npm install @vantigo/career-score

Quick Start

const { computeCareerScore } = require('@vantigo/career-score');

const result = computeCareerScore({
  pctile:        75,         // Salary at 75th percentile
  aiRisk:        22,         // Low AI automation risk
  timingVerdict: 'act-now',  // Hot job market
  marketDemand:  68,         // Strong hiring demand
});

console.log(result);
// {
//   score: 79,
//   band: 'Strong',
//   color: '#34D399',
//   components: {
//     compensation: 75,
//     aiResilience: 78,
//     growth: 85,
//     demand: 68
//   }
// }

Formula

Career Score = round(
  0.35 × compensation  +   // salary percentile rank
  0.25 × AI_resilience +   // 100 − aiRisk.score
  0.20 × growth        +   // market timing (act-now=85, prepare=55, wait=30)
  0.20 × demand            // market demand score
)

Weight Rationale

| Component | Weight | Rationale | |---|---|---| | Compensation | 35% | Salary position is the primary signal of career health | | AI Resilience | 25% | Automation risk is the defining career risk of the 2020s | | Growth / Timing | 20% | Market timing affects whether job switching is financially optimal | | Market Demand | 20% | Demand predicts negotiation leverage and job security |

Score Bands

| Score | Band | Meaning | |---|---|---| | 85–100 | Excellent | Well-compensated, resilient to automation, strong market | | 70–84 | Strong | Above average in most dimensions | | 50–69 | Average | Targeted improvements recommended | | 30–49 | Needs Attention | Undercompensated or high automation risk | | 0–29 | Critical | Multiple risk factors; immediate action recommended |

API

computeCareerScore(params) → result

Parameters:

| Parameter | Type | Description | |---|---|---| | pctile | number | Salary percentile rank (0–100) | | aiRisk | number | AI automation risk score (0–100); will be inverted to resilience | | timingVerdict | string|number | "act-now" | "prepare" | "wait" or numeric (0–100) | | marketDemand | number | Market demand score (0–100) |

Returns:

| Field | Type | Description | |---|---|---| | score | number | Career Score integer (0–100) | | band | string | Score band label | | color | string | Hex color for the band | | components | object | Individual component scores for transparency |

computeCareerScoreFromReport(report) → result | null

Convenience wrapper that accepts a full Vantigo report JSON object.

const { computeCareerScoreFromReport } = require('@vantigo/career-score');

const result = computeCareerScoreFromReport({
  market: { pctile: 75 },
  aiRisk: { score: 22 },
  timing: { verdict: 'act-now' },
  marketDemand: 68,
});

Validation

Validated against 10 occupation profiles spanning technology, healthcare, education, law, and skilled trades. See docs/methodology.md for full validation table.

Citation

If you use this package in academic research, please cite:

@software{ogirala2026careerscore,
  author = {Ogirala, Kranthi Kumar},
  title  = {Vantigo Career Score: A Multi-Dimensional Career Health Metric},
  year   = {2026},
  url    = {https://github.com/ogkranthi/earnmore},
  note   = {npm package @vantigo/career-score}
}

See also: arXiv preprint (link to be added upon submission)

Related Packages

• @vantigo/bls-soc-map — BLS SOC code lookup from free-text job titles
• @vantigo/geo-arbitrage — Net take-home geographic arbitrage calculator

License

MIT © Kranthi Kumar Ogirala / Vantigo