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Model Risk Management Jobs in California (NOW HIRING)

East West Bank

AI Governance

Pasadena, CA · On-site

$130K/yr

Support regulatory, audit, model risk, and enterprise risk management activities related to AI and advanced analytics environments. * Translate governance policies into repeatable operational ...

East West Bank

AI Governance

Pasadena, CA

Support regulatory, audit, model risk, and enterprise risk management activities related to AI and advanced analytics environments. * Translate governance policies into repeatable operational ...

East West Bank

AI Governance

Pasadena, CA · On-site

$130K/yr

Support regulatory, audit, model risk, and enterprise risk management activities related to AI and advanced analytics environments. * Translate governance policies into repeatable operational ...

Chumash Enterprises

Risk Manager

Santa Ynez, CA · On-site

This role and its function are part of the Risk Management shared services model. A Team Member in a shared service structure, works within a dedicated business unit (including people, processes, and ...

Chumash Enterprises

Risk Manager

Santa Ynez, CA

$99K - $124K/yr

This role and its function are part of the Risk Management shared services model. A Team Member in a shared service structure, works within a dedicated business unit (including people, processes, and ...

The TCW Group

Risk Lead

Los Angeles, CA · On-site

$200K - $250K/yr

Chair or actively participate in risk review meetings with portfolio managers and senior leadership. Portfolio Risk Framework : * Define and maintain portfolio risk metrics, methodologies, and models ...

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Model Risk Management information

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$36K

$81.3K

$136.2K

How much do model risk management jobs pay per year?

As of Jul 9, 2026, the average yearly pay for model risk management in California is $81,252.00, according to ZipRecruiter salary data. Most workers in this role earn between $61,700.00 and $89,300.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Model Risk Management position, and why are they important?

To excel in Model Risk Management, a professional needs a strong grounding in quantitative finance, statistics, and risk assessment, often backed by advanced degrees in relevant fields. Familiarity with technical tools such as Python, R, SAS, and model validation platforms, along with relevant certifications like FRM or CFA, is highly beneficial. Exceptional communication skills, attention to detail, and critical thinking help individuals stand out when interacting with model developers and risk committees. Mastery of these abilities ensures thorough risk analysis, regulatory compliance, and effective mitigation of financial model risks within the organization.

What are some common challenges faced by professionals in Model Risk Management roles?

Professionals in Model Risk Management commonly encounter challenges such as evolving regulatory requirements, the complexity of advanced financial models, and ensuring effective communication between technical and non-technical stakeholders. Staying current with industry best practices while rigorously validating and documenting models can be demanding but is critical for reducing financial and operational risks. Team members often work cross-functionally, collaborating closely with quants, risk managers, and IT teams to evaluate model performance and implement improvements. Adapting to new analytical tools and maintaining a proactive approach to emerging risks will help you succeed and grow in this dynamic field.

What is a Model Risk Management job?

A Model Risk Management (MRM) job involves identifying, assessing, and mitigating risks associated with financial and analytical models used by an organization. Professionals in this role ensure models are accurate, reliable, and comply with regulatory requirements by conducting validation, testing, and performance monitoring. They work closely with model developers, risk teams, and auditors to manage model lifecycle processes. Strong quantitative, analytical, and regulatory knowledge are key skills for success in this field.

What are the most commonly searched types of Model Risk Management jobs in California? The most popular types of Model Risk Management jobs in California are:
What are popular job titles related to Model Risk Management jobs in California? For Model Risk Management jobs in California, the most frequently searched job titles are:
What job categories do people searching Model Risk Management jobs in California look for? The top searched job categories for Model Risk Management jobs in California are:
What cities in California are hiring for Model Risk Management jobs? Cities in California with the most Model Risk Management job openings:
Model Risk Management jobs near you
AI Governance

AI Governance

East West Bank

Pasadena, CA • On-site

$130K/yr

Full-time

Re-posted 4 days ago

Job description

Introduction
Since 1973, East West Bank has served as a pathway to success. With over 110 locations across the U.S. and Asia, we are the premier financial bridge between the East and West. Our teams of experienced, multi-cultural professionals help guide businesses and community members on both sides of the Pacific looking to explore new markets and create new opportunities, and our sustained growth and expertise in industries like real estate, entertainment and media, private equity and venture capital, and high-tech help build sustainable businesses and expand our associates' potential for career advancement.
Headquartered in California, East West Bank (Nasdaq: EWBC) is a top-performing commercial bank with a strong foundation, an enterprising spirit and a commitment to absolute integrity. East West Bank gives people the confidence to reach further.
Overview
East West Bank is seeking a highly experienced AI Governance to lead the design, implementation, and operationalization of the bank's enterprise AI governance framework. This role is designed for a hands-on governance leader with deep expertise in AI governance, data governance, risk management, and regulatory compliance within highly regulated industries. The ideal candidate combines practical implementation experience with strong understanding of AI/ML technologies, enterprise controls, data risk, model risk, operational governance, and responsible AI practices. The role will partner across business, technology, data, legal, risk, compliance, audit, and operations teams to establish scalable governance processes supporting AI use cases from intake through production monitoring and enterprise adoption. This position is part of East West Bank's Enterprise AI Strategy & Transformation organization, focused on scaling AI initiatives into governed, measurable, compliant, and enterprise-ready capabilities.
Responsibilities
  • Lead the design and implementation of the enterprise AI governance framework, operating model, standards, controls, and governance processes.
  • Establish and operationalize governance processes for AI intake, inventory management, prioritization, risk assessment, technology gating, approval workflows, monitoring, issue remediation, and value realization tracking.
  • Drive governance activities across the full AI lifecycle including ideation, proof of concept, pilot, production deployment, monitoring, model review, and retirement.
  • Partner with business, technology, data, legal, risk, compliance, cybersecurity, and audit teams to ensure AI initiatives align with enterprise governance standards and regulatory expectations.
  • Define governance controls for AI-enabled solutions including data quality, lineage, privacy, explainability, human oversight, auditability, retention, access governance, and operational resiliency.
  • Establish AI governance reporting, dashboards, metrics, and executive-level transparency related to AI adoption, business value, risk exposure, control effectiveness, and remediation progress.
  • Lead governance processes related to LLM, Generative AI, RAG, intelligent automation, and advanced analytics solutions.
  • Evaluate AI technologies, platforms, and vendors to ensure alignment with enterprise architecture, security, compliance, operational, and risk standards.
  • Support regulatory, audit, model risk, and enterprise risk management activities related to AI and advanced analytics environments.
  • Translate governance policies into repeatable operational procedures, evidence requirements, controls, checklists, and implementation standards.
  • Promote enterprise AI governance awareness, adoption, and responsible AI practices across business and technology organizations.
  • Perform other duties as assigned.

Qualifications
  • 8+ years of experience in AI governance, data governance, model risk, enterprise risk, compliance, data management, or related governance disciplines within financial services, fintech, insurance, or other highly regulated industries.
  • Strong hands-on experience designing and implementing enterprise AI governance frameworks and operational governance processes in production environments.
  • Demonstrated experience operationalizing AI governance across AI intake, inventory management, prioritization, technology assessment/gating, risk assessment, approvals, monitoring, remediation, and value/metrics reporting.
  • Deep understanding of AI risk, model risk, data risk, operational risk, privacy, explainability, bias, human oversight, and responsible AI principles.
  • Strong understanding of regulatory, compliance, audit, and governance expectations related to AI, model governance, data governance, and enterprise controls.
  • Hands-on experience governing AI/ML, LLM, Generative AI, RAG, and advanced analytics solutions within enterprise environments.
  • Strong familiarity with enterprise governance tooling including Microsoft Purview, Collibra, Alation, Informatica, MLflow, model registries, monitoring platforms, and AI observability solutions.
  • Practical understanding of cloud data and AI ecosystems including Azure, Databricks, Snowflake, AWS, GCP, and modern data platforms.
  • Strong understanding of metadata management, data lineage, access governance, data lifecycle management, retention, and enterprise data quality controls.
  • Experience partnering across business, technology, risk, compliance, legal, cybersecurity, audit, and operations teams to operationalize governance at scale.
  • Strong analytical, executive communication, and stakeholder management skills with the ability to translate complex AI and governance risks into actionable business decisions.
  • Bachelor's degree in Information Systems, Computer Science, Data Management, Risk Management, Business Analytics, or related discipline.

Highly Preferred
  • Direct experience governing enterprise AI/GenAI programs within banking or highly regulated industries.
  • Strong familiarity with banking regulatory frameworks and governance expectations including SR 11-7, BCBS 239, CCAR, CECL, AML/BSA, privacy, and enterprise risk management standards.
  • Experience governing LLM platforms including OpenAI, Azure OpenAI, Anthropic Claude, Gemini, Bedrock, or open-source models.
  • Hands-on experience with AI governance related to RAG architectures, vector databases, AI monitoring, prompt governance, and model evaluation frameworks.
  • Experience implementing governance controls supporting AI explainability, fairness, auditability, monitoring, and evidence management.
  • Strong understanding of AI/ML lifecycle management, MLOps, model registries, and production monitoring frameworks.
  • Professional certifications such as CDMP, DAMA, Collibra, Microsoft Purview, risk management, or AI governance certifications.
  • Master's degree or advanced degree in Data Management, AI, Risk Management, Computer Science, or related quantitative discipline.

Applicants must have legal authorization to work in the United States. We do not offer visa sponsorship at this time.
Compensation
The base pay range for this position is USD $130,000.00/Yr. - USD $185,000.00/Yr. Exact offers will be determined based on job-related knowledge, skills, experience, and location.

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