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Contract Model Risk Governance Jobs in California

Adobe

Sr. Manager Risk & Governance

San Jose, CA

Lead Adobe's Security Risk and Governance program by advancing the security risk strategy through ... Improve decision-making using security insights, data analytics, and modeling to validate the ...

Adobe, Inc.

Sr. Manager Risk & Governance

San Jose, CA · On-site

Lead Adobe's Security Risk and Governance program by advancing the security risk strategy through ... Improve decision-making using security insights, data analytics, and modeling to validate the ...

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 ...

Unavailable

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 ...

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 ...

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Contract Model Risk Governance information

What are some common challenges faced by professionals in Contract Model Risk Governance roles, and how can they be addressed?

Professionals in Contract Model Risk Governance often encounter challenges such as keeping up with evolving regulatory requirements, ensuring thorough model documentation, and effectively communicating risk findings to both technical and non-technical stakeholders. Balancing the need for detailed model validation with tight project timelines can also be demanding. To address these challenges, it's important to foster strong cross-functional collaboration, stay updated on industry best practices, and develop clear communication strategies for reporting risk and compliance issues.

What is the difference between Contract Model Risk Governance vs Contract Model Validation?

AspectContract Model Risk GovernanceContract Model Validation
Primary FocusOverseeing and managing risks associated with contract models, ensuring compliance and risk mitigationAssessing and testing contract models to ensure accuracy and reliability
ResponsibilitiesEstablishing policies, monitoring risk exposure, and implementing controlsPerforming independent reviews, testing model assumptions, and validating outputs
Work EnvironmentRisk management teams, compliance departments, regulatory interactionsQuantitative teams, model validation units, audit functions

While Contract Model Risk Governance focuses on managing and overseeing risks related to contract models, Contract Model Validation involves the technical assessment and testing of those models to ensure their accuracy and reliability. Both roles are essential in a comprehensive risk management framework within financial institutions and industries relying on contract models.

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

To excel in Contract Model Risk Governance, you need a strong background in risk management, quantitative analysis, and familiarity with regulatory requirements, often supported by a degree in finance, mathematics, or a related field. Proficiency with risk management software, model validation tools, and knowledge of frameworks such as SR 11-7 is typically required. Attention to detail, critical thinking, and effective communication are crucial soft skills for evaluating model risk and collaborating with stakeholders. These skills ensure robust oversight of model risk, regulatory compliance, and support sound decision-making within financial institutions.

What is Contract Model Risk Governance?

Contract Model Risk Governance refers to the framework and processes used by organizations to identify, assess, monitor, and mitigate risks associated with the use of models in contracts or contractual obligations. This role ensures that the use of quantitative models in financial and business contracts complies with regulatory standards and internal policies, reducing the likelihood of errors, misinterpretations, or financial losses. Professionals in this field often oversee model validation, implementation, and documentation, and work closely with compliance, risk, and legal teams. Effective governance helps maintain model integrity and supports sound decision-making across the organization.
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Contract Model Risk Governance jobs near you

Senior Model Risk Manager - AI/ML

Mercury

San Francisco, CA • On-site, Remote

Full-time

Posted 13 days ago

Job description

Mercury is building the financial stack - intuitive, powerful, and safe for entrepreneurs and businesses of all sizes. We have made a deliberate, company-wide bet on AI/ML. Across fraud detection, financial crime prevention, credit decisioning, and internal operations, machine learning and AI models are becoming core to how Mercury works, and that portfolio is growing fast.
As AI transforms financial services, every institution is being forced to ask a hard question: what does model risk management (MRM) actually mean in this new era? ML has powered fraud detection and credit decisioning for years, but the scope and technology has changed dramatically. Generative models, autonomous agents, and real-time systems are creating risks that existing MRM frameworks were never designed to govern. No one has fully solved this yet. We want to hire the person who will. Ideal candidates may come from a traditional model validation background with deep hands-on experience testing modern AI/ML systems, or from model development, applied AI, or research as data scientists, with a strong understanding of how risks emerge in complex systems and how to rigorously challenge them as they scale into production.
*Mercury is a fintech company, not an FDIC-insured bank. Banking services provided through Choice Financial Group and Column N.A., Members FDIC.
As Senior Model Risk Manager - AI/ML, you will define what model governance looks like for AI/ML at Mercury. That means continuously building and enhancing the frameworks, not just inheriting them. You will own validation, monitoring, and governance of Mercury's AI/ML model portfolio, but more than that, you will be a thought leader in an industry-wide conversation about how MRM must evolve in the context of AI. You will partner closely with data scientists, engineers, compliance leads, and product teams, and you will help shape not just Mercury's approach, but set a standard for what rigorous, forward-looking MRM on AI can look like in fintech.
Here are some of the things you will do:
Model Governance & Monitoring Oversight
  • Maintain and enhance Mercury's model governance framework, including inventory standards, documentation templates, validation standards, and issue management.
  • Assess whether first-line monitoring efforts are effective, proportionate to model risk, and sufficient to keep models fit for purpose over time.

Model Validation
  • Perform independent validation across predictive ML models, generative AI systems, and agentic workflows, covering data, assumptions, methodology, testing, and monitoring.
  • Assess risks in LLM-powered applications, including RAG pipelines, tool use, autonomy boundaries, human oversight, and hallucination risk.
  • Identify and document model limitations, failure modes, and emerging AI risks including drift, instability, fairness, and robustness concerns

MRM Advisory
  • Serve as a trusted advisor to data scientists, engineers, product teams, and risk partners throughout the AI/ML lifecycle to provide practical guidance on model risk, governance expectations, and control design without slowing responsible innovation.
  • Evaluate new AI use cases for regulatory implications, materiality, and governance requirements prior to deployment.
  • Help shape Mercury's responsible AI standards, including explainability, bias assessment, testing, human oversight, and documentation.

AI Enablement for MRM
  • Develop and maintain AI-enabled automation tools to improve the speed, scale, and effectiveness of model governance and validation workflows.
  • Modernize the MRM function to operate effectively in a fast-moving AI environment while maintaining strong governance standards.

Culture and Advocacy
  • Champion MRM as a strategic enabler of safe and scalable AI/ML adoption, not simply a control function.
  • Build model risk literacy across engineering, product, data science, compliance, and risk teams.

There are many paths that could lead you here. We think the strongest candidates will bring some combination of the following:
  • Bachelor's degree in a quantitative field (e.g. Computer Science, Engineering, Statistics, Mathematics, etc.) with 6-10 years of meaningful hands-on experience developing or validating AI/ML models and systems, ideally in financial services or fintech.
  • Strong technical foundations in Python, SQL, and modern ML tooling (e.g. scikit-learn, XGBoost); familiarity with LLMs, RAG systems, prompt engineering, and AI agent frameworks.
  • Experience in evaluating and testing machine learning models (e.g. in fraud detection) and generative AI systems, including custom evals, red-teaming, or frameworks.
  • Solid understanding of model risk governance principles and regulatory expectations (e.g. SR 11-7 / OCC 2011-12, SR 26-2).
  • Deep appreciation of disciplined model governance and independent effective challenge.
  • A healthy dose of skepticism combined with a constructive, solution-oriented approach.
  • Comfort operating in ambiguity: capable of synthesizing fragmented technical, operational, and business context into a clear understanding of how complex models and AI systems actually work, and making sound judgments even without a complete playbook or perfect documentation.
  • High agency and adaptability: able to operate effectively in a fast-moving environment where priorities evolve quickly, new ad hoc problems emerge regularly, and role boundaries are intentionally broad. You can operate effectively without tightly-defined scope, find the highest-leverage work, and get it done.
  • Exceptional attention to detail across documentation, code base, testing artifacts and quantitative analysis.
  • Strong written and verbal communication skills; you can explain model risk to a data scientist and to a regulator, and use different language for each.

The total rewards package at Mercury includes base salary, equity, and benefits.
Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry. New hire offers are made based on a candidate's experience, expertise, geographic location, and internal pay equity relative to peers.
Our target new hire base salary ranges for this role are the following:
  • US employees (any location): $200,700 - $250,900
  • Canadian employees (any location): CAD $189,700 - $237,100

Mercury values diversity & belonging and is proud to be an Equal Employment Opportunity employer. All individuals seeking employment at Mercury are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation, or any other legally protected characteristic. We are committed to providing reasonable accommodations throughout the recruitment process for applicants with disabilities or special needs. If you need assistance, or an accommodation, please let your recruiter know once you are contacted about a role.
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