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Chief Model Risk Officer Jobs (NOW HIRING)

PA · On-site

Chief Risk Officer (CRO)** will report directly to the CEO with a dotted line to the Risk and Audit ... model validation, KYC (know your customer) and quantitative analytics. The CRO will account for ...

This position will report to the L&A Risk Officer, with an indirect reporting relationship to the Model Risk Officer. As the ALM modeling infrastructure at Fortitude continues to mature, this ...

We are seeking a Chief Risk Officer (CRO) to join our executive team. The CRO will identify, assess and mitigate significant competitive, regulatory, and technological threats to our organization ...

This position will report to the L&A Risk Officer, with an indirect reporting relationship to the Model Risk Officer. As the ALM modeling infrastructure at Fortitude continues to mature, this ...

Hybrid work model: flexible arrangements for most positions * Benefits Packages, including Medical ... The CRO serves as the principal risk advisor to the CEO and the Board of Directors, ensuring that ...

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Chief Model Risk Officer information

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$99K

$191.8K

$384K

How much do chief model risk officer jobs pay per year?

As of Sep 11, 2026, the average yearly pay for chief model risk officer in the United States is $191,763.00, according to ZipRecruiter salary data. Most workers in this role earn between $168,500.00 and $190,500.00 per year, depending on experience, location, and employer.

What is a chief model risk officer?

Chief Model Risk Officers (CMROs) are senior executives responsible for overseeing and managing an organization’s model risk management framework. They ensure that all models used for decision-making, such as those for credit, market, and operational risk, are accurate, reliable, and compliant with regulatory standards. CMROs lead teams that validate models, assess their performance, and establish policies to mitigate risks associated with model errors or misuse. Their role is crucial in industries like banking and finance, where models play a significant part in risk assessment and strategic planning.

How does a chief model risk officer typically collaborate with other departments to ensure effective model governance?

A Chief Model Risk Officer (CMRO) frequently works with teams such as quantitative analysts, IT, compliance, and internal audit to establish and maintain comprehensive model governance frameworks. This collaboration ensures that all models used across the organization are properly validated, monitored, and comply with regulatory requirements. The CMRO often leads cross-functional committees, communicates risk assessments, and provides recommendations to senior management, fostering a culture of transparency and accountability in model use. Effective partnership with these departments is essential for identifying potential model risks early and implementing robust controls.

What are the key skills and qualifications needed to thrive as a chief model risk officer, and why are they important?

To thrive as a Chief Model Risk Officer, you need deep expertise in quantitative modeling, risk management, and regulatory compliance, usually supported by advanced degrees in finance, mathematics, or related fields. Familiarity with risk management frameworks, statistical software (such as SAS, R, or Python), and regulatory requirements like SR 11-7 is essential. Strong leadership, strategic thinking, and communication skills help drive effective governance and collaboration across departments. These competencies are crucial to ensure the integrity of models, mitigate financial risk, and maintain regulatory compliance within the organization.

What is the difference between Chief Model Risk Officer vs Quantitative Analyst?

AspectChief Model Risk OfficerQuantitative Analyst
CredentialsAdvanced degrees in finance, statistics, or related fields; certifications like FRM or CFADegree in mathematics, finance, or engineering; often CFA or CQF
Work EnvironmentSenior leadership, risk management departments, strategic decision-makingFinancial institutions, trading desks, model development teams
Industry UsageRegulatory compliance, risk oversight, model validation

The Chief Model Risk Officer focuses on overseeing and managing model risks at an organizational level, ensuring compliance and risk mitigation. In contrast, a Quantitative Analyst primarily develops and calibrates financial models to support trading, risk assessment, or investment decisions. While both roles require strong quantitative skills and relevant certifications, the Chief Model Risk Officer operates at a strategic, risk management level, whereas the Quantitative Analyst is more involved in model development and analysis.

What are popular job titles related to Chief Model Risk Officer jobs?

For Chief Model Risk Officer jobs, the most frequently searched job titles are:

Infographic showing various Chief Model Risk Officer job openings in the United States as of September 2026, with employment types broken down into 2% As Needed, 83% Full Time, 13% Part Time, and 2% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $191,763 per year, or $92.2 per hour.

Artificial Intelligence (AI) Data Governance Officer

Fishers, IN • On-site

Full-time

Re-posted 7 days ago


Key responsibilities

  • Administers the Bank's enterprise AI governance framework and supporting procedures.

  • Coordinates activities across business lines and corporate functions related to AI use cases.

  • Assesses proposed AI implementations to determine applicable governance requirements and controls.


Job description

IN0534 Fishers, OH0523 Independence Bus Office, OH0713 NW Bancshares HQ, PA0258 Bellevue, PA0736 Administration Center

Job Description

The AI Governance Officer is a senior-level contributor responsible for administering the Bank's enterprise AI governance framework and supporting the oversight of artificial intelligence use cases throughout their lifecycle. The role exercises sound judgment in assessing AI-related risks, facilitating risk-based governance decisions, coordinating cross-functional review processes, and ensuring compliance with internal standards and regulatory expectations. The position plays a critical role in enabling responsible innovation while maintaining transparency, accountability, and effective oversight of AI capabilities deployed across the institution.
Essential Functions
Leads administration of the Bank's enterprise AI risk governance framework and supporting procedures. Coordinates activities across all business lines and corporate functions.
Coordinate intake, assessment, and governance activities for proposed AI use cases. Determine and document the classification of solutions as models, agents, tools, job aids, or other categories defined by policy.
Serve coordinator for the AI Working Group, including preparation of agendas, meeting materials, decision logs, and action item tracking.
Maintain the enterprise inventory of AI use cases and associated governance records.
Assess proposed AI implementations to determine applicable governance requirements and control expectations.
Develop management reporting and dashboards related to AI inventory, approvals, issues, and emerging risks. Monitor compliance with AI governance standards and escalate material issues to executive leadership.
Promote awareness and understanding of AI governance requirements throughout the institution.
Develops and maintains enterprise policies, standards, and procedures governing AI risk.
Serve as a senior member of the Model Risk team, exercising sound judgment in evaluating model risk and making decisions on model approvals and issue closures as a delegate of the Chief Model Risk Officer.
Participate in the research and evaluation of emerging modeling techniques, including AI/ML, and assess their applicability and risk implications within the institution.
Contribute to the development and enhancement of the model risk management framework, including validation methodologies, documentation standards, and governance practices.
Review academic and industry research, summarize key insights, and propose practical applications to improve model risk oversight and innovation.
Ensure compliance with Northwest's policies and procedures, as well as applicable federal and state regulations including SR26-2, interagency AI/ML guidance, and the U.S. Treasury Financial Services AI Risk Management Framework.
Interprets evolving regulatory expectations relating to artificial intelligence and translates them into practical governance requirements.
Serves as the primary coordinator for regulatory examinations, audits, and independent reviews of AI governance.
Additional Essential Functions
Ensure compliance with Northwest's policies and procedures, and Federal/State regulations
Navigate Microsoft Office Software, computer applications, and software specific to the department in order to maximize technology tools and gain efficiency
Work as part of a team
Work with on-site equipment

What You Bring to the Team

Participate in enterprise initiatives involving emerging technologies and advanced analytics.
Own the design, implementation, and enhancement of governance workflows within Archer or similar systems.
Recommend customer service enhancements
QUALIFICATIONS
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
Education
Bachelor's Degree Undergraduate degree in risk management, business, economics, statistics, mathematics, information systems, computer science, law, or related discipline.
Master's Degree Master's degree in risk management, business, economics, statistics, mathematics, information systems, computer science, law, or related discipline.
Work Experience
8 - 12 years Experience in a financial institution or consulting environment, with demonstrated exposure to AI governanceAnd
3 - 5 years Experience evaluating or governing AI/ML use cases across the lifecycle, including:
pre-implementation assessment
control design
post-deployment monitoring
Experience with generative AI, machine learning, or decision-support systems, including understanding of associated risks (e.g., bias, explainability, data dependency, automation risk)
Experience supporting or interacting with internal audit, regulators, or independent model review functions
Experience supporting or interacting with internal audit, regulators, or independent model review functions
Additional Knowledge, Skills and Abilities
Ability to apply risk-based judgment in ambiguous situations, particularly in evaluating AI use cases where regulatory expectations and governance standards are evolving
Ability to analyze complex AI/ML concepts and communicate risks, limitations, and trade-offs clearly to both technical and non-technical stakeholders
Ability to challenge and influence business and technology stakeholders to ensure appropriate risk identification, control design, and governance outcomes
Ability to identify patterns, emerging risks, and systemic issues across multiple AI use cases rather than evaluating them in isolation.
Ability to make sound governance decisions in gray areas, including classification (model vs agent vs tool), control requirements, and escalation thresholds
Ability to coordinate cross-functional governance processes and drive clear outcomes across Risk, Technology, Compliance, Legal, and Business teams
Ability to develop and interpret risk metrics, monitoring outputs, and performance indicators for AI systems
Licenses and Certifications
Certified Information Systems Auditor (CISA)
Certified in Risk and Information Systems Control (CRISC)
Financial Risk Manager (FRM)
Certified Third-Party Risk Professional (CTPRP)
Relevant AI governance certifications

Northwest is an equal opportunity employer. We are committed to creating an inclusive environment for all employees.