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model risk management jobs in 2026 — demand, top roles hiring, and related skills

As of 2026-09-30, model risk management appears in 221 job postings indexed by Skillenai over the past 90 days — Data Scientist has the most postings mentioning model risk management, with demand share up 0.9% vs the prior 4 weeks.

Last updated · 90d ending 2026-09-30

Postings · last 90 days
221
Demand vs prior month
up 0.9% vs the prior 4 weeks
Top role · 8.1% of skill postings
Data Scientist
Top hiring metro
New York City

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Frequently asked questions about model risk management

+Is model risk management in demand in 2026?

Yes. model risk management appears in 221 job postings indexed by Skillenai over the 90 days ending 2026-09-30. Data Scientist accounts for the most postings mentioning model risk management (8.1% of all postings mentioning model risk management).

+What jobs require model risk management?

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 risk management are Quantitative Finance Analyst (63.6% of that role’s postings mention model risk management), AI Governance Lead (26.1% of that role’s postings mention model risk management), AI Product Owner (9.7% of that role’s postings mention model risk management).

+What skills are commonly paired with model risk management?

Across job postings indexed by Skillenai (90 days ending 2026-09-30), model risk management most often appears alongside machine learning, Python, AI governance, model validation, responsible AI.

+Where is model risk management most in demand?

As of 2026-09-30, the metro areas posting the most jobs requiring model risk management are New York City, Toronto, London, Chicago, Arlington, according to the Skillenai jobs index.

+How can I keep up with new model risk management content and jobs?

Skillenai indexes news, blog posts, and research papers mentioning model risk management alongside the jobs index. You can subscribe to a daily email digest of new model risk management content from your Skillenai account.

+Which skills come before and after model risk management?

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 risk management — last 90 days

Career paths around model risk management

Skills documented before and after this skill across employer changes.

Historical career profiles · all locations

Skills before model risk management

Before model risk managementmachine learning → model risk management: 2 observed employer moves with this skill pairrisk management system → model risk management: 1 observed employer moves with this skill pairkeyword research tool → model risk management: 1 observed employer moves with this skill pairstatistical models → model risk management: 1 observed employer moves with this skill pairR Programming → model risk management: 1 observed employer moves with this skill pairreporting processes → model risk management: 1 observed employer moves with this skill pairsql → model risk management: 1 observed employer moves with this skill pairOffice 365 → model risk management: 1 observed employer moves with this skill pairmodel riskmanagementmachine learning: 2 movesmachine learning2 movesrisk management system: 1 movesrisk managementsystem1 moveskeyword research tool: 1 moveskeyword researchtool1 movesstatistical models: 1 movesstatistical models1 movesR Programming: 1 movesR Programming1 movesreporting processes: 1 movesreportingprocesses1 movessql: 1 movessql1 movesOffice 365: 1 movesOffice 3651 moves

Skills after model risk management

After model risk managementmodel risk management → ad hoc reporting: 1 observed employer moves with this skill pairmodel risk management → MRR: 1 observed employer moves with this skill pairmodel risk management → Machine Learning recommenders: 1 observed employer moves with this skill pairmodel risk management → segmentation analysis: 1 observed employer moves with this skill pairmodel risk management → CNN: 1 observed employer moves with this skill pairmodel risk management → heteroskedasticity: 1 observed employer moves with this skill pairmodel risk management → RNN: 1 observed employer moves with this skill pairmodel risk management → GBDT: 1 observed employer moves with this skill pairmodel riskmanagementad hoc reporting: 1 movesad hoc reporting1 movesMRR: 1 movesMRR1 movesMachine Learning recommenders: 1 movesMachine Learningrecommenders1 movessegmentation analysis: 1 movessegmentationanalysis1 movesCNN: 1 movesCNN1 movesheteroskedasticity: 1 movesheteroskedasticity1 movesRNN: 1 movesRNN1 movesGBDT: 1 movesGBDT1 moves
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.

Observed connections and move counts
ConnectionMoves
Before: machine learning2
Before: risk management system1
Before: keyword research tool1
Before: statistical models1
Before: R Programming1
Before: reporting processes1
Before: sql1
Before: Office 3651
After: ad hoc reporting1
After: MRR1
After: Machine Learning recommenders1
After: segmentation analysis1
After: CNN1
After: heteroskedasticity1
After: RNN1
After: GBDT1

Roles most likely to require model risk management

Among roles with at least 20 postings in the same period.

RolePostings mentioning skill% of role postings mentioning skill
Quantitative Finance Analyst1463.6%
AI Governance Lead626.1%
AI Product Owner39.7%
Quantitative Risk Analyst29.1%
AI Data Scientist15.0%
AI Lead14.5%
Product Management Director14.3%
AI Research Intern14.2%
Business Consultant14.2%
Cybersecurity Consultant44.0%

Roles with the most model risk management postings

RolePostings mentioning skillShare of skill postings
Data Scientist188.1%
Quantitative Finance Analyst146.3%
AI Governance Lead62.7%
AI Governance & Regulatory Risk Expert52.3%
AI Governance Manager52.3%
Cybersecurity Consultant41.8%
Machine Learning Risk Management Lead41.8%
Product Manager41.8%
Program Manager41.8%
AI Architect31.4%

Top companies posting jobs requiring model risk management

Employers ranked by indexed job postings in the last 90 days.

Top companies posting jobs requiring model risk management
CompanyPostings · 90 days
Capco17
Ghr15
USAA9
Barclays7
Affirm7
Manulife6
Wf4
Nubank4
State Street4
Staffnixcom4

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 risk management

NamePostingsShare
New York City115.0%
Toronto94.1%
London83.6%
Chicago62.7%
Arlington52.3%
Plano41.8%
Buffalo31.4%
Charlotte31.4%
Hong Kong31.4%

Skills commonly paired with model risk management

machine learning (68)Python (64)AI governance (63)model validation (56)responsible AI (45)SQL (44)data governance (43)Generative AI (41)model governance (29)model development (28)

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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 risk management by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s model risk management postings by all model risk management 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
a3689f036d7b054f
data_as_of
2026-09-30
window_days
90
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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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Compiled by Jared Rand · Data sourced from the Skillenai labor market index