Data Science
Providers using this tag (96)
Ranked by API Evangelist rating — Exemplar and Strong are expanded by default.
Strong 10 Solid coverage with minor gaps
Developing 17 Usable, with meaningful gaps to close
Thin 15 Limited public surface area
Emerging 28 Early or largely undocumented
Minimal 24 Almost no public developer surface
Unrated 2 Not yet scored
APIs with this tag (13)
Ranked by the provider's API Evangelist rating — the Kin Score is scored per provider, not per API, so every API of a provider shares its band. How the rating works →
Exemplar 2 Complete, well-documented, and agent-ready
Strong 2 Solid coverage with minor gaps
Developing 3 Usable, with meaningful gaps to close
Thin 3 Limited public surface area
Emerging 2 Early or largely undocumented
Minimal 1 Almost no public developer surface
Companies reaching this through an API (9)
These companies publish an API, specification or operation carrying “Data Science” but do not classify their business under it. Listed unranked and kept out of the count above, because one tagged operation is not a statement about what a company does.
Score breakdown
Related tags
Where this tag comes from
Markets provisional
Kin Score markets whose measured providers carry this tag. Share is the fraction of the market's measured providers that carry it — it describes the market, not this tag.
| Market | Share of the market's providers |
|---|---|
| Official R Client Packages on CRAN | 27% |
Cohort brief
Auto-generatedThe 84 providers in the APIs.io catalog tagged Data Science, scored on the Kin Score. Every figure below is computed from the catalog — nothing here is written.
| Facet | This cohort | Catalog | Difference | Scored |
|---|---|---|---|---|
| Developer Ergonomics | 34 | 24.5 | +9.5 | 84 |
| Operational Transparency | 16.6 | 13.2 | +3.4 | 84 |
| Access Clarity | 32.7 | 30 | +2.7 | 84 |
| Contract Quality | 19.3 | 18.6 | +0.7 | 84 |
| Discoverability | 59.6 | 59.1 | +0.5 | 84 |
| Contract Governance | 9.7 | 9.7 | 0 | 84 |
A facet is averaged over the members that carry it, not over the whole cohort — the “Scored” column is that count. Averaging an absent facet as zero would score our own coverage gaps as the providers’ posture.
| Artifact | This cohort | Catalog | Difference |
|---|---|---|---|
| MCP server (any) | 21% | 18% | +3 |
| MCP server (first-party) | 21% | 16% | +5 |
| Agent Skills | 0% | 0% | 0 |
| OAuth scopes | 15% | 13% | +2 |
| Security | 95% | 99% | -4 |
| Arazzo workflows | 1% | 1% | 0 |
| Governance rules | 33% | 36% | -3 |
mcp_pct counts any mcp/ artifact including ones API Evangelist derived from the provider OpenAPI; mcp_first_party_pct counts only servers the provider publishes. Prefer the latter.
- 1 Anaconda 63.4
- 2 Hex 63.3
- 3 Posit 62.5
- 4 DataRobot 60.7
- 5 H2O.ai 59.2
- 6 Dataiku 58.2
- 7 Akkio 56.8
- 8 Ledger Investing 55.2
- 9 Quadrillion 55.2
- 10 Anomaly Detection 54.6
- 1 Hex 55.9
- 2 Prior Labs 54.8
- 3 DataRobot 51.5
- 4 Helena Bioinformatics 44.3
- 5 Deepnote 43.9
- 6 H2O.ai 40.6
- 7 Anaconda 39.8
- 8 Google Colab 36.7
- 9 Nixtla 33.8
- 10 Probabl 32.6
Coverage caveat. 72 of 84 scored members had under half their catalog-attributable points satisfied at all (catalog_earned / catalog_max < 0.5). They are INCLUDED in the mean above. A large share here means the cohort mean is partly a measurement of how far our enrichment reached, not only of how these providers publish.Generated from the catalog build of 14 November 2026, across 41591 providers, using the same computation served by the APIs.io cohort API. Briefs are published for rosters of 5 or more scored providers; below that a distribution is not meaningful.
Work with this as data
Every tag here is available over the APIs.io API and to AI agents over MCP.