clustering jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-09-28, clustering appears in 739 job postings indexed by Skillenai over the past 90 days — Data Scientist has the most postings mentioning clustering, with demand down 16% vs the prior 4 weeks.
Last updated · 90d ending 2026-09-28
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Frequently asked questions about clustering
+Is clustering in demand in 2026?
Yes. clustering appears in 739 job postings indexed by Skillenai over the 90 days ending 2026-09-28, with demand down 16% vs the prior 4 weeks. Data Scientist accounts for the most postings mentioning clustering (35.9% of all postings mentioning clustering).
+What jobs require clustering?
According to the Skillenai jobs index over the 90 days ending 2026-09-28, among roles with at least 20 postings, the highest shares mentioning clustering are Product Data Scientist (19.0% of that role’s postings mention clustering), Data & Analytics Engineer (9.5% of that role’s postings mention clustering), SQL Database Administrator (8.7% of that role’s postings mention clustering).
+What skills are commonly paired with clustering?
Across job postings indexed by Skillenai (90 days ending 2026-09-28), clustering most often appears alongside Python, SQL, classification, machine learning, regression.
+Where is clustering most in demand?
As of 2026-09-28, the metro areas posting the most jobs requiring clustering are New York City, Bengaluru, London, Berlin, Broomfield, according to the Skillenai jobs index.
+How can I keep up with new clustering content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning clustering alongside the jobs index. You can subscribe to a daily email digest of new clustering content from your Skillenai account.
Weekly job postings requiring clustering — last 90 days
Salary distribution
Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized
Roles most likely to require clustering
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| Product Data Scientist | 12 | 19.0% |
| Data & Analytics Engineer | 2 | 9.5% |
| SQL Database Administrator | 2 | 8.7% |
| Principal Data Scientist | 3 | 7.7% |
| Database Architect | 2 | 7.4% |
| Data Science Analyst | 2 | 5.7% |
| Data Science Consultant | 4 | 5.6% |
| Data Science Intern | 2 | 4.9% |
| Data Scientist | 265 | 4.8% |
| Marketing Data Scientist | 1 | 4.8% |
Roles with the most clustering postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| Data Scientist | 265 | 35.9% |
| Software Engineer | 51 | 6.9% |
| Data Engineer | 36 | 4.9% |
| Machine Learning Engineer | 27 | 3.7% |
| Data Analyst | 22 | 3.0% |
| Database Administrator | 20 | 2.7% |
| Product Data Scientist | 12 | 1.6% |
| ML Engineer | 11 | 1.5% |
| Product Data Science Manager | 11 | 1.5% |
| Systems Engineer | 11 | 1.5% |
Top metros hiring for clustering
| Name | Postings | Share |
|---|---|---|
| New York City | 18 | 2.4% |
| Bengaluru | 16 | 2.2% |
| London | 15 | 2.0% |
| Berlin | 12 | 1.6% |
| Broomfield | 12 | 1.6% |
| San Francisco | 10 | 1.4% |
| Amsterdam | 9 | 1.2% |
| Mountain View | 8 | 1.1% |
| Warsaw | 8 | 1.1% |
Skills commonly paired with clustering
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How this was computed
Counts derive from the Skillenai jobs index over the 90 days ending 2026-09-28. Skills are resolved against the Skillenai canonical taxonomy, so the same entity is counted whether a posting writes 'Python', 'Python 3', or 'python'. Role prevalence divides postings mentioning clustering by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s clustering postings by all clustering postings, including postings without a role. Shares need not sum to 100% for the displayed roles. Pages refresh weekly (or daily for the top-50 most-requested skills).
- source
- Skillenai jobs index, deduplicated daily
- entity_id
- c4577c77460224b9
- data_as_of
- 2026-09-28
- window_days
- 90
The demand, skills, and geo numbers on this page come from the same Skillenai labor market index that powers our API. Use it for compensation benchmarking, hiring-competition analysis, and skill-adoption tracking.
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