model validation jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-09-30, model validation appears in 754 job postings indexed by Skillenai over the past 90 days — Data Scientist has the most postings mentioning model validation, with demand share up 11.6% vs the prior 4 weeks.
Last updated · 90d ending 2026-09-30
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Frequently asked questions about model validation
+Is model validation in demand in 2026?
Yes. model validation appears in 754 job postings indexed by Skillenai over the 90 days ending 2026-09-30. Data Scientist accounts for the most postings mentioning model validation (25.6% of all postings mentioning model validation).
+What jobs require model validation?
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 validation are Quantitative Finance Analyst (63.6% of that role’s postings mention model validation), Quantitative Risk Analyst (40.9% of that role’s postings mention model validation), Senior Data Scientist (14.8% of that role’s postings mention model validation).
+What skills are commonly paired with model validation?
Across job postings indexed by Skillenai (90 days ending 2026-09-30), model validation most often appears alongside Python, machine learning, SQL, model monitoring, feature engineering.
+Where is model validation most in demand?
As of 2026-09-30, the metro areas posting the most jobs requiring model validation are New York City, London, Long Beach, San Francisco, Washington, according to the Skillenai jobs index.
+How can I keep up with new model validation content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning model validation alongside the jobs index. You can subscribe to a daily email digest of new model validation content from your Skillenai account.
+Which skills come before and after model validation?
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 validation — last 90 days
Salary distribution
Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized
Career paths around model validation
Skills documented before and after this skill across employer changes.
Historical career profiles · all locations
Skills before model validation
Skills after model validation
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: python | 2 |
| Before: sql | 2 |
| Before: Amazon Redshift | 2 |
| Before: ¹³C | 1 |
| Before: ci/cd | 1 |
| Before: ETL | 1 |
| Before: a/b testing | 1 |
| Before: x-ray crystallography | 1 |
| After: K-means clustering | 1 |
| After: ci/cd | 1 |
| After: ETL | 1 |
| After: visualizations | 1 |
| After: a/b testing | 1 |
| After: vector databases | 1 |
| After: Data ingestion | 1 |
| After: Data quality | 1 |
Roles most likely to require model validation
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| Quantitative Finance Analyst | 14 | 63.6% |
| Quantitative Risk Analyst | 9 | 40.9% |
| Senior Data Scientist | 4 | 14.8% |
| Machine Learning Manager | 3 | 12.0% |
| Quantitative Analyst | 13 | 11.2% |
| Data Science Director | 6 | 10.3% |
| Industrial Engineer | 2 | 9.5% |
| Simulation Engineer | 3 | 8.8% |
| AI Governance Lead | 2 | 8.7% |
| Principal Data Scientist | 3 | 7.5% |
Roles with the most model validation postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| Data Scientist | 193 | 25.6% |
| Machine Learning Engineer | 50 | 6.6% |
| AI/ML Engineer | 14 | 1.9% |
| Quantitative Finance Analyst | 14 | 1.9% |
| ML Engineer | 13 | 1.7% |
| Quantitative Analyst | 13 | 1.7% |
| AI Engineer | 11 | 1.5% |
| Spacecraft Propulsion Systems Engineer | 10 | 1.3% |
| Quantitative Risk Analyst | 9 | 1.2% |
| Research Scientist | 9 | 1.2% |
Top companies posting jobs requiring model validation
Employers ranked by indexed job postings in the last 90 days.
| Company | Postings · 90 days |
|---|---|
| Capital One | 17 |
| Barclays | 15 |
| Ghr | 14 |
| Grafanalabs | 13 |
| Vanguard | 13 |
| Bosch | 13 |
| RocketHub | 12 |
| Monzo | 12 |
| CBA | 12 |
| Waymo | 10 |
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 validation
| Name | Postings | Share |
|---|---|---|
| New York City | 42 | 5.6% |
| London | 30 | 4.0% |
| Long Beach | 19 | 2.5% |
| San Francisco | 12 | 1.6% |
| Washington | 11 | 1.5% |
| Chicago | 10 | 1.3% |
| Singapore | 10 | 1.3% |
| Hyderabad | 9 | 1.2% |
| Mountain View | 8 | 1.1% |
Skills commonly paired with model validation
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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 validation by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s model validation postings by all model validation 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: 0.3% to 0.3%. 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 2,596 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
- 2b9c9faa083ee5dc
- 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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