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datamatastudios/skill-demand-index

Datamata Skill Demand Index Daily share of active tech job listings mentioning each skill, across data, engineering, product, DevOps, security and AI. One row per category and skill from the most recent snapshot, including how often each skill is a hard requirement. Latest snapshot: 2026-10-10 Rows in this release: 732 Updated: daily Licence: CC BY 4.0 — free to use and adapt, including commercially, with attribution. Source & methodology:… See the full description on the dataset page: https://huggingface.co/datasets/datamatastudios/skill-demand-index.

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Datamata Skill Demand Index

Daily share of active tech job listings mentioning each skill, across data, engineering, product, DevOps, security and AI. One row per category and skill from the most recent snapshot, including how often each skill is a hard requirement.

  • —Latest snapshot: 2026-10-10
  • —Rows in this release: 732
  • —Updated: daily
  • —Licence: CC BY 4.0 — free to use and adapt, including commercially, with attribution.
  • —Source & methodology: <https://www.datamatastudios.com/datasets>

Quickstart

python
import pandas as pd

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

# Highest-demand skills right now
print(df.sort_values("demand_pct", ascending=False).head(10))

Or load it with the 🤗 datasets library:

python
from datasets import load_dataset

ds = load_dataset("datamatastudios/skill-demand-index")

What you can answer with it

  • —Which skills lead demand in data, engineering, product, DevOps, security or AI — and by how much.
  • —How often a skill is a hard requirement versus nice-to-have (required_count vs listing_count).
  • —How a skill's demand share moves over time, by appending each daily snapshot.

Columns

ColumnTypeDescription
snapshot_datestringUTC date the snapshot was computed (YYYY-MM-DD).
categorystringRole category: data, engineering, product, devops, security or ai.
skillstringNormalised skill name.
skill_groupstringSkill family the skill belongs to (e.g. language, cloud, framework).
listing_countnumberActive listings in the category that mention the skill.
total_listingsnumberTotal active listings in the category on that date.
demand_pctnumberlistingcount / totallistings x 100, rounded to 0.1.
required_countnumberListings where the skill is a hard requirement (vs nice-to-have). Blank for rows snapshotted before this was tracked.

How it is built

Active tech job listings are scraped daily from public applicant-tracking systems (Greenhouse, Lever, Ashby) and aggregated boards. For each role category the demand share of a skill is listings_with_skill / total_active_listings x 100. This release is the most recent daily snapshot for all six categories. Full method and known limitations: <https://www.datamatastudios.com/methodology>.

Citation

Datamata Studios. "Datamata Skill Demand Index." 2026-10-10. https://www.datamatastudios.com/datasets. Licensed under CC BY 4.0.