scikit-learn jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-09-28, scikit-learn appears in 2,140 job postings indexed by Skillenai over the past 90 days — Data Scientist has the most postings mentioning scikit-learn, with demand down 46% vs the prior 4 weeks.
Last updated · 90d ending 2026-09-28
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Frequently asked questions about scikit-learn
+Is scikit-learn in demand in 2026?
Yes. scikit-learn appears in 2,140 job postings indexed by Skillenai over the 90 days ending 2026-09-28, with demand down 46% vs the prior 4 weeks. Data Scientist accounts for the most postings mentioning scikit-learn (28.9% of all postings mentioning scikit-learn).
+What jobs require scikit-learn?
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 scikit-learn are Applied Value Engineer (50.0% of that role’s postings mention scikit-learn), Senior Data Scientist (30.8% of that role’s postings mention scikit-learn), AI/ML Architect (26.9% of that role’s postings mention scikit-learn).
+What skills are commonly paired with scikit-learn?
Across job postings indexed by Skillenai (90 days ending 2026-09-28), scikit-learn most often appears alongside Python, PyTorch, TensorFlow, pandas, SQL.
+Where is scikit-learn most in demand?
As of 2026-09-28, the metro areas posting the most jobs requiring scikit-learn are New York City, London, Bengaluru, Toronto, San Francisco, according to the Skillenai jobs index.
+How can I keep up with new scikit-learn content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning scikit-learn alongside the jobs index. You can subscribe to a daily email digest of new scikit-learn content from your Skillenai account.
Weekly job postings requiring scikit-learn — last 90 days
Salary distribution
Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized
Roles most likely to require scikit-learn
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| Applied Value Engineer | 20 | 50.0% |
| Senior Data Scientist | 8 | 30.8% |
| AI/ML Architect | 7 | 26.9% |
| Applied AI Scientist | 6 | 21.4% |
| Value Engineer | 10 | 20.8% |
| AI/ML Engineer | 63 | 19.6% |
| Machine Learning Engineer | 311 | 13.6% |
| AI/ML Scientist | 3 | 13.0% |
| Quantitative Research Intern | 3 | 13.0% |
| Artificial Intelligence Engineer | 3 | 12.5% |
Roles with the most scikit-learn postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| Data Scientist | 619 | 28.9% |
| Machine Learning Engineer | 311 | 14.5% |
| AI Engineer | 110 | 5.1% |
| ML Engineer | 99 | 4.6% |
| Software Engineer | 89 | 4.2% |
| AI/ML Engineer | 63 | 2.9% |
| Data Engineer | 43 | 2.0% |
| Solutions Architect | 30 | 1.4% |
| Data Analyst | 27 | 1.3% |
| Applied Value Engineer | 20 | 0.9% |
Top metros hiring for scikit-learn
| Name | Postings | Share |
|---|---|---|
| New York City | 84 | 3.9% |
| London | 55 | 2.6% |
| Bengaluru | 54 | 2.5% |
| Toronto | 50 | 2.3% |
| San Francisco | 48 | 2.2% |
| Chicago | 34 | 1.6% |
| Singapore | 31 | 1.4% |
| Pune | 30 | 1.4% |
| Hyderabad | 26 | 1.2% |
Skills commonly paired with scikit-learn
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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 scikit-learn by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s scikit-learn postings by all scikit-learn 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
- 06f2958dbbc57f1e
- 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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