---
license: cc-by-4.0
pretty_name: Datamata Skill Scarcity Index
language:
  - en
tags:
  - jobs
  - labor-market
  - skills
  - hiring-trends
  - salaries
  - recruiting
size_categories:
  - n<10K
source_datasets:
  - original
configs:
  - config_name: default
    data_files: skill-scarcity-index.csv
---

![Datamata Skill Scarcity Index](dataset-cover-image.png)

# Datamata Skill Scarcity Index

Which tech skills are genuinely hard to hire for: a daily composite scarcity score per skill built from how long roles stay open (time-to-fill), the salary premium employers pay over the category median and how often the same role is re-posted after failing to fill. Computed from active job listings across public company career pages and job boards.

- **Latest snapshot:** 2026-08-05
- **Rows in this release:** 4933
- **Updated:** daily
- **Licence:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) — free to use and adapt, including commercially, with attribution.
- **Source & methodology:** <https://www.datamatastudios.com/datasets/skill-scarcity-index>

## Quickstart

```python
import pandas as pd

# Stream straight from the Hub — no download step needed
df = pd.read_csv("hf://datasets/datamatastudios/skill-scarcity-index/skill-scarcity-index.csv")

# Headline: hardest-to-hire data skills right now
latest = df[df.snapshot_date == df.snapshot_date.max()]
print(
    latest[latest.category == "data"]
    .sort_values("scarcity_score", ascending=False)
    [["skill_name", "scarcity_score", "median_days_open", "salary_premium_pct"]]
    .head(10)
)
```

Or load it with the 🤗 `datasets` library:

```python
from datasets import load_dataset

ds = load_dataset("datamatastudios/skill-scarcity-index")
```

## What you can answer with it

- Which skills keep roles open longest — and whether that gap is widening.
- Which skills command a salary premium over their category median.
- Which skills employers repeatedly fail to hire for (repost rate).
- How scarcity is shifting as AI skills flood into job requirements.

## What's NOT in this file (live on the site)

The composite score is here in full. Three deeper cuts are computed from the
same pipeline but only published interactively:

- **Company adoption feed** — the first date each company started hiring for
  each skill ("47 companies added Iceberg to job requirements this quarter"):
  <https://www.datamatastudios.com/datasets/skill-scarcity-index>
- **Stack combinations** — which skill *triples* (e.g. AWS + dbt + Snowflake)
  actually appear together in postings, monthly.
- **Time-to-fill by role and seniority** — the same lifespan metric cut by
  role rather than skill.

## Columns

| Column | Type | Description |
|---|---|---|
| `snapshot_date` | string | UTC date the snapshot was taken (YYYY-MM-DD). |
| `category` | string | Job category: data, engineering, product, devops, security or ai. |
| `skill_name` | string | Canonical skill name from the extraction taxonomy. |
| `demand_count` | number | Active listings mentioning the skill on the snapshot date. |
| `demand_pct` | number | demand_count as a percentage of all active listings in the category. |
| `median_days_open` | number | Median days recently-closed listings with this skill stayed open. Blank below the sample floor. |
| `salary_premium_pct` | number | Median disclosed salary of listings with this skill vs the category median, in percent. Blank below the sample floor. |
| `repost_rate_pct` | number | Share of this skill's listings that are re-posts of an earlier identical role (a failed-hire signal). |
| `scarcity_score` | number | 0-100 weighted percentile-rank composite of the three components within the category. Higher = harder to hire. |

## How it is built

Each day we snapshot every active job listing scraped from public company
career pages and job boards, extract skills with a curated taxonomy and
combine three hard-to-hire signals per skill: median lifespan of closed
listings (time-to-fill), median disclosed salary vs the category median and
the share of listings that are re-posts of an earlier identical role. The
score is a weighted percentile-rank composite within each category, so scores
are comparable across categories. Full method and known limitations:
<https://www.datamatastudios.com/methodology>.

## Citation

> Datamata Studios. "Datamata Skill Scarcity Index." 2026-08-05. https://www.datamatastudios.com/datasets/skill-scarcity-index. Licensed under CC BY 4.0.