model governance jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-09-30, model governance appears in 338 job postings indexed by Skillenai over the past 90 days — Data Scientist has the most postings mentioning model governance, with demand share up 5.0% vs the prior 4 weeks.
Last updated · 90d ending 2026-09-30
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Frequently asked questions about model governance
+Is model governance in demand in 2026?
Yes. model governance appears in 338 job postings indexed by Skillenai over the 90 days ending 2026-09-30. Data Scientist accounts for the most postings mentioning model governance (12.7% of all postings mentioning model governance).
+What jobs require model governance?
According to the Skillenai jobs index over the 90 days ending 2026-09-30, among roles with at least 20 postings, the highest shares mentioning model governance are Lead Data Scientist (10.0% of that role’s postings mention model governance), AI Engineering Director (9.4% of that role’s postings mention model governance), Quantitative Finance Analyst (9.1% of that role’s postings mention model governance).
+What skills are commonly paired with model governance?
Across job postings indexed by Skillenai (90 days ending 2026-09-30), model governance most often appears alongside Python, machine learning, SQL, model validation, MLOps.
+Where is model governance most in demand?
As of 2026-09-30, the metro areas posting the most jobs requiring model governance are London, Boston, San Francisco, Toronto, New York City, according to the Skillenai jobs index.
+How can I keep up with new model governance content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning model governance alongside the jobs index. You can subscribe to a daily email digest of new model governance content from your Skillenai account.
+Which skills come before and after model governance?
The skill-flow chart shows skills documented in adjacent positions across observed employer changes. An outgoing skill is documented in the following position but not the preceding one. These are ideas to explore, not proven prerequisites, acquisition dates, or levels of mastery. Each ribbon counts employer moves with that skill pair; one move can contribute several pairs.
Weekly indexed postings requiring model governance — last 90 days
Salary distribution
Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized
Career paths around model governance
Skills documented before and after this skill across employer changes.
Historical career profiles · all locations
Skills before model governance
Skills after model governance
How to read this chart · view counts
Each side is an independent set of observed employer moves, not the same people followed through three stages. Ribbon widths compare move counts within that side. Internal moves are not included.
The following position documents a skill that the preceding position does not. Skills must be linked to both positions, with clear dates and no overlap. One move can connect several skill pairs. These patterns suggest skills to explore; they do not establish prerequisites, when a skill was learned, or a higher skill level.
Source: Skillenai talent graph, historical career profiles. Historical descriptions and coverage can change. Only the leading published connections are shown.
| Connection | Moves |
|---|---|
| Before: a/b testing | 2 |
| Before: NLP | 1 |
| Before: Churn-Prediction | 1 |
| Before: LLM-based applications | 1 |
| Before: exploratory data analysis (EDA) | 1 |
| Before: sql | 1 |
| Before: Amazon Redshift | 1 |
| Before: Flan-T5 | 1 |
| After: ci/cd | 1 |
| After: Azure DevOps | 1 |
| After: a/b testing | 1 |
| After: Azure Data Factory (ADF) | 1 |
| After: YAML | 1 |
| After: CDC | 1 |
| After: cloud-native tools | 1 |
| After: production monitoring | 1 |
Roles most likely to require model governance
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| Lead Data Scientist | 10 | 10.0% |
| AI Engineering Director | 5 | 9.4% |
| Quantitative Finance Analyst | 2 | 9.1% |
| Quantitative Risk Analyst | 2 | 9.1% |
| AI Governance Lead | 2 | 8.7% |
| Chief Technology Officer | 4 | 8.5% |
| Machine Learning Manager | 2 | 8.0% |
| ML Engineering Manager | 2 | 7.7% |
| Data Science Director | 3 | 5.2% |
| Principal Consultant | 1 | 5.0% |
Roles with the most model governance postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| Data Scientist | 43 | 12.7% |
| AI Engineer | 16 | 4.7% |
| Machine Learning Engineer | 11 | 3.3% |
| Lead Data Scientist | 10 | 3.0% |
| Data Science Manager | 8 | 2.4% |
| Product Manager | 7 | 2.1% |
| Systems Engineer | 6 | 1.8% |
| AI Engineering Director | 5 | 1.5% |
| AI/ML Engineer | 5 | 1.5% |
| AI Architect | 4 | 1.2% |
Top companies posting jobs requiring model governance
Employers ranked by indexed job postings in the last 90 days.
| Company | Postings · 90 days |
|---|---|
| Axial Search | 10 |
| Capital One | 9 |
| JPMorgan Chase & Co. | 9 |
| Mastercard | 8 |
| Staffnixcom | 7 |
| Mercury | 7 |
| LBG | 7 |
| CBA | 6 |
| Manulife | 6 |
| Vanguard | 5 |
Job postings indexed over the past 90 days, grouped by resolved employer. Counts are postings, not hires. Companies without a published page appear without a link.
Top metros hiring for model governance
| Name | Postings | Share |
|---|---|---|
| London | 24 | 7.1% |
| Boston | 9 | 2.7% |
| San Francisco | 8 | 2.4% |
| Toronto | 8 | 2.4% |
| New York City | 7 | 2.1% |
| Chicago | 6 | 1.8% |
| Jersey City | 6 | 1.8% |
| Pune | 5 | 1.5% |
| Bengaluru | 4 | 1.2% |
Skills commonly paired with model governance
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How this was computed
Counts derive from the Skillenai jobs index over the 90 days ending 2026-09-30. 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 model governance by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s model governance postings by all model governance 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). Adjusted posting share: 0.1% to 0.1%. Demand share change is the relative percentage change between these adjusted shares. Each employer-and-ATS group has at least 10 postings in each 90-day window; its earlier posting count supplies the same weight in both windows. The panel includes 2,595 identified employers and covers 68% of earlier and 72% of latest indexed postings. Windows: 2026-06-02 to 2026-08-31 and 2026-06-30 to 2026-09-28 (UTC; end dates excluded). The windows overlap by 62 days. Dates reflect indexing, not the employer’s posting date. This measures posting mix, not total hiring or market-wide demand. Matching excludes entrants and exits; changes in crawl completeness within an employer or ATS can still affect the result.
- source
- Skillenai jobs index, deduplicated daily
- entity_id
- b85ed7da4f68c618
- data_as_of
- 2026-09-30
- 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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