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Director Model Risk Governance Jobs in Michigan (NOW HIRING)

... governance model for AI use across the enterprise. This role partners closely with the AI ... risk, responsible AI attributes, versioning, metadata, and lifecycle status are maintained ...

Enterprise Architect (IT)

Detroit, MI · On-site +1

$68.25 - $88/hr

Reporting to the Director of Enterprise Architecture, this role partners with business, technology ... Familiarity with AI governance, model risk considerations, responsible AI principles, data ...

Enterprise Architect (IT)

Detroit, MI · On-site +1

$102K - $208K/yr

Reporting to the Director of Enterprise Architecture, this role partners with business, technology ... Familiarity with AI governance, model risk considerations, responsible AI principles, data ...

Collaborate with security, legal, and governance teams to ensure responsible AI, privacy, and ... Establish guardrails for responsible AI: data privacy, model risk, transparency, bias awareness ...

Showing results 21-40

Director Model Risk Governance information

What is a director model risk governance?

Director Model Risk Governance roles are senior positions responsible for overseeing and managing the risks associated with financial and predictive models within an organization. These professionals establish and implement model risk management frameworks, ensure compliance with regulatory requirements, and oversee model validation processes. They collaborate with model developers, validators, and business units to identify, assess, and mitigate model risks, as well as report on governance effectiveness to senior management. Their work is crucial in maintaining the reliability and integrity of models used for decision-making and regulatory reporting.

What are the key skills and qualifications needed to thrive as a director model risk governance?

To thrive as a Director of Model Risk Governance, you need deep expertise in quantitative finance, risk management, and model validation, often backed by an advanced degree in a quantitative field and relevant industry experience. Familiarity with risk management frameworks, regulatory standards (e.g., SR 11-7), and proficiency in analytical tools like Python, R, or SAS are typically required. Exceptional leadership, communication, and critical thinking skills help you effectively oversee teams and coordinate with stakeholders across the organization. These competencies are vital to ensure robust model governance, regulatory compliance, and informed risk-based decision-making at the enterprise level.

What are some common challenges faced by a director model risk governance, and how can they be addressed?

A Director of Model Risk Governance often encounters challenges such as ensuring consistent model validation across diverse business units, keeping up with evolving regulatory requirements, and fostering effective communication between model owners, validators, and senior management. Addressing these challenges typically involves establishing robust model risk frameworks, maintaining clear documentation, and promoting a culture of transparency and collaboration. Regular training sessions and open forums can help bridge knowledge gaps, while leveraging technology can streamline model inventory and validation processes.

What is the difference between Director Model Risk Governance vs Model Risk Analyst?

AspectDirector Model Risk GovernanceModel Risk Analyst
CredentialsAdvanced degrees (e.g., Master’s, PhD), professional certifications (e.g., FRM, CFA)Bachelor’s or Master’s degree, relevant certifications
Work EnvironmentStrategic oversight, policy development, senior stakeholder engagementData analysis, model validation, risk assessment
Employer & Industry UsageFinancial institutions, banks, asset managersFinancial institutions, risk management teams
Search & Comparison IntentUnderstanding leadership roles in model risk governanceEntry to mid-level model risk roles, analysis tasks

The main difference is that the Director Model Risk Governance focuses on strategic oversight, policy setting, and managing model risk at a senior level, while the Model Risk Analyst handles technical validation, data analysis, and risk assessment tasks. The director role involves leadership and decision-making, whereas the analyst role is more technical and operational.

What are the most commonly searched types of Model Risk Governance jobs in Michigan?

The most popular types of Model Risk Governance jobs in Michigan are:

What job categories do people searching Director Model Risk Governance jobs in Michigan look for?

The top searched job categories for Director Model Risk Governance jobs in Michigan are:

What cities in Michigan are hiring for Director Model Risk Governance jobs?

Cities in Michigan with the most Director Model Risk Governance job openings:

Infographic showing various Director Model Risk Governance job openings in Michigan as of August 2026, with employment types broken down into 2% As Needed, 80% Full Time, 14% Part Time, 3% Contract, and 1% Nights. Highlights an 88% Physical, 5% Hybrid, and 7% Remote job distribution.

Full-time

Re-posted 26 days ago


Corning rating

8.2

Company rating: 8.2 out of 10

Based on 128 frontline employees who took The Breakroom Quiz

90th of 540 rated manufacturers


Job description

AI Governance Operations Analyst 

Are you looking to be part of a global innovator in materials science, where your work can shape the future of connectivity, technology, and everyday experiences?

What is your role?
The AI Governance & Responsible AI Program Analyst supports the enterprise AI governance function and helps operationalize a scalable, guardrail-based governance model for AI use across the enterprise. This role partners closely with the AI Governance Lead and works across technical teams, legal, security, privacy, and business stakeholders. The position focuses on AI intake, use case classification, control validation, and maintaining centralized governance records and documentation.

  Major responsibilities and tasks of the position:
- Coordinate and manage AI use case intake, classification, tracking, and review across business units, including governance dimensions such as domain, data sensitivity, autonomy level, audience, geography, platform, and regulatory exposure.


- Map incoming AI requests to standardized domain guardrails; identify required controls, existing controls, and control gaps; validate control implementation, ownership, oversight, supporting evidence, remediation actions, and approval conditions; and maintain governance workflows, decision records, and audit-ready documentation.


- Assist in the creation, review, and publication of model cards and related AI documentation for traditional ML and generative AI use cases, ensuring standards for transparency, explainability, risk, responsible AI attributes, versioning, metadata, and lifecycle status are maintained.


- Develop and maintain responsible AI templates, checklists, guidance, and “how-to” materials; help define and evolve domain-specific guardrail libraries; standardize governance artifacts; define end-user responsibilities within the control framework; and collaborate with cross-functional teams including Finance, HR, Legal, Engineering, Cyber, Privacy, and Platform.

What do you need to have?
- Bachelor’s degree in a related field such as technology, policy, information systems, data, or similar, or equivalent experience
- Strong organizational skills with the ability to manage multiple workstreams and stakeholders
- Ability to understand and summarize technical concepts without being a hands-on model developer
- Clear written communication skills and attention to detail
- Experience in AI, data, digital, privacy, security, or technology governance
- Familiarity with AI/ML concepts or responsible AI principles
- Experience with workflow tools, controls, or audit documentation

 What we offer?
- Great benefits above law
- Growing environment that supports learning
- Opportunity to work with global stakeholders across business and technical teams
- Exposure to enterprise AI governance, responsible AI practices, and cross-functional collaboration

Corning is committed to providing equal employment opportunities and considers requests for reasonable accommodations in accordance with applicable laws. Individuals with disabilities or sincerely held religious beliefs may request reasonable accommodation to participate in the application or interview process, perform essential job functions, or access other benefits and privileges of employment. To submit a request for reasonable accommodations related to disability or religion, please contact us at accommodations@corning.com

Corning is committed to providing equal employment opportunities and considers requests for reasonable accommodations in accordance with applicable laws. Individuals with disabilities or sincerely held religious beliefs may request reasonable accommodations to participate in the application or interview process, perform essential job functions, or access other benefits and privileges of employment. To submit a request for reasonable accommodation related to disability or religion, please contact us at accommodations@corning.com.


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