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Model Risk Manager Jobs in Houston, TX (NOW HIRING)

Support and provide model development for pricing, valuation, and risk metrics using historical and forecast market data. * Manage enhancements, configurations, and user support for the PCI ETRM ...

Serve as subject matter expert on AI technologies, including large language models and emerging AI ... Strong judgment and risk assessment capability * Experience working cross-functionally with IT and ...

The position is based in Downtown Houston with a hybrid work model of 3 days in the office and 2 ... Project Risk Framework Leadership: * Design, implement, and govern the Project Risk Management ...

As part of the risk desk enabling the growth of Chariot/Hanwha Energy USA's business, this role ... management for decision-making purposes * Preparing financial models and data mining tools for ...

As part of the risk desk enabling the growth of Chariot/Hanwha Energy USA's business, this role ... management for decision-making purposes * Preparing financial models and data mining tools for ...

As part of the risk desk enabling the growth of Chariot/Hanwha Energy USA's business, this role ... management for decision-making purposes * Preparing financial models and data mining tools for ...

Risk Analyst

Houston, TX

$93.60K - $114.40K/yr

Support scenario modeling, maintain internal controls, and offer recommendations to managers, ensuring activities align with risk policies and regulatory requirements. * Partner with commercial ...

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Showing results 1-20

Model Risk Manager information

See Houston, TX salary details

$49.2K

$106.5K

$162.3K

How much do model risk manager jobs pay per year?

As of May 31, 2026, the average yearly pay for model risk manager in Houston, TX is $106,533.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,900.00 and $123,200.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Model Risk Manager, and why are they important?

To thrive as a Model Risk Manager, you need a solid background in quantitative finance, statistics, or mathematics, often supported by an advanced degree and experience in model development or validation. Familiarity with programming languages such as Python or R, risk management frameworks, and regulatory requirements like SR 11-7 or ECB guidelines is typically expected. Strong analytical thinking, attention to detail, and effective communication are crucial soft skills for articulating complex model risks to stakeholders. These competencies are vital for ensuring the accuracy, compliance, and reliability of financial models within an organization.

What are some common challenges a Model Risk Manager faces when validating complex financial models?

Model Risk Managers often encounter challenges such as limited or incomplete data, evolving regulatory requirements, and the need to validate highly complex or proprietary models. They must work closely with model developers, quantitative analysts, and compliance teams to ensure all assumptions and methodologies are sound. Staying up to date with industry best practices and maintaining clear documentation are also crucial, as is effectively communicating findings to both technical and non-technical stakeholders.

What does a Model Risk Manager do?

A Model Risk Manager is responsible for identifying, assessing, and mitigating risks associated with financial and analytical models used by an organization. They ensure that models are accurate, reliable, and compliant with regulatory standards by overseeing validation processes and monitoring model performance. Their role often includes collaborating with model developers, conducting independent reviews, and implementing model governance frameworks to minimize potential losses or errors stemming from model misuse or inaccuracies.

What is the difference between Model Risk Manager vs Quantitative Analyst?

AspectModel Risk ManagerQuantitative Analyst
Required CredentialsAdvanced degrees in finance, statistics, or mathematics; certifications like FRM or CFADegree in finance, economics, mathematics, or related fields; often CFA or CQF
Work EnvironmentFocus on risk management teams within financial institutions; regulatory complianceAnalytical roles within trading, investment, or banking divisions; model development
Employer & Industry UsageFinancial institutions, banks, asset managersInvestment firms, hedge funds, banks, financial services

The Model Risk Manager primarily oversees and mitigates risks associated with financial models, ensuring compliance and accuracy. In contrast, Quantitative Analysts develop and implement models to support trading, investment, or risk strategies. While both roles require strong quantitative skills and similar credentials, their focus areas differ—risk management versus model development and analysis.

What are popular job titles related to Model Risk Manager jobs in Houston, TX? For Model Risk Manager jobs in Houston, TX, the most frequently searched job titles are:
What job categories do people searching Model Risk Manager jobs in Houston, TX look for? The top searched job categories for Model Risk Manager jobs in Houston, TX are:
What cities near Houston, TX are hiring for Model Risk Manager jobs? Cities near Houston, TX with the most Model Risk Manager job openings:
Infographic showing various Model Risk Manager job openings in Houston, TX as of May 2026, with employment types broken down into 1% As Needed, 95% Full Time, 3% Part Time, and 1% Contract. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $106,533 per year, or $51.2 per hour.
Cyber AI Governance and Privacy Senior Consultant

Cyber AI Governance and Privacy Senior Consultant

Deloitte

Houston, TX • On-site

Other

Posted 19 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

58th of 138 rated financial services


Job description

We are seeking an AI Governance and Privacy Specialist who can operationalize responsible AI in real systems-especially agentic AI and LLM-enabled applications. This role blends governance and privacy expertise with enough software development fluency to create developer-ready guidance, implement controls-as-code patterns, and stand up measurable evaluation and monitoring workflows.

As a Senior Consultant, you will help clients and internal delivery teams move from AI principles to practices: risk tiering, model and agent inventories, technical guardrails, governance workflows integrated into the SDLC, and evidence artifacts suitable for audits and regulators.

Recruiting for this role ends on 6/5/2026.

Work You'll Do

You will lead and deliver AI governance, privacy, and security outcomes across the AI lifecycle, including:

  • Designing pragmatic AI governance operating models (intake, risk tiering, approvals, documentation standards, exception handling, and audit readiness) with a focus on GenAI and agentic AI deployments.
  • Building and maintaining AI system inventories (models, agents, tools, data sources, integrations), with clear ownership, intended use, risk classification, and change-control expectations.
  • Conducting AI risk assessments for privacy, security, model risk, and misuse-including prompt injection, sensitive data exposure, excessive agency, and overreliance-and translating findings into implementable mitigations.
  • Establishing technical control guidance for teams building agentic AI solutions: human-in-the-loop patterns, tool access controls, safe retrieval and grounding practices, logging/monitoring, token and data minimization, and incident response playbooks.
  • Implementing "governance in the workflow" by integrating governance checkpoints into product and engineering delivery (architecture reviews, release gates, evaluation requirements, documentation automation, and evidence capture).
  • Standing up or enhancing evaluation and monitoring approaches for GenAI systems: test plans, safety and quality metrics, red teaming workflows, and reporting dashboards for leaders and risk stakeholders.
  • Partnering cross-functionally with Cybersecurity, Privacy, Legal, Risk, Engineering, and Data Science to drive adoption and ensure governance guidance is usable, measurable, and repeatable.

The Team

You will join a cross-functional group working at the intersection of cyber, privacy, governance, and emerging AI delivery. The team helps organizations scale AI responsibly by combining governance and engineering patterns so teams can innovate faster without compromising trust.

Qualifications

Required

  • Bachelor's degree or equivalent practical experience.
  • 4+ years of experience in one or more of the following: AI governance, data privacy, security risk management, compliance and controls, AI product risk, model risk management, or technology risk consulting.
  • Demonstrated experience translating policies and regulatory expectations into operational workflows, artifacts, and controls (e.g., intake processes, inventories, decision logs, risk registers, RACI, playbooks).
  • Working knowledge of AI/ML/LLM systems and delivery lifecycles sufficient to assess real deployment risks and mitigations (training vs. RAG vs. fine-tuning vs. tool use, data dependencies, integration patterns).
  • Software development fluency: ability to collaborate with engineering teams on implementation details; ability to prototype or automate governance workflows in Python/SQL and to understand CI/CD and cloud deployment basics.
  • Practical experience with privacy program execution and artifacts (PIAs/DPIAs, vendor reviews, data inventories, data minimization, retention, and access control principles).
  • Ability to communicate clearly with both technical and non-technical stakeholders and produce executive-ready reporting.
  • Ability to travel 0-50%, on average, based on client and project needs.
  • Limited immigration sponsorship may be available.

Preferred

  • Previous consulting or Big 4 experience.
  • Hands-on experience operationalizing AI governance aligned to frameworks such as the NIST AI RMF and/or ISO/IEC 42001, with awareness of risk-based AI regulatory regimes (e.g., EU AI Act).
  • Experience with GenAI safety and evaluation practices (prompt injection testing, jailbreak resilience, hallucination measurement, toxicity/harm scoring, grounding effectiveness).
  • Familiarity with governance tooling and workflow platforms (e.g., OneTrust, GRC platforms, ticketing/workflow systems) and how to integrate them into engineering delivery.
  • Certifications such as CIPP/US, CIPM, IAPP AIGP, CISM, or CISSP.
  • Prior experience in cyber or enterprise security contexts (data security, identity, audit logging, secure SDLC).
  • Experience designing Human-in-the-Loop escalation pathways, exception handling, and automated safety protocols for highly autonomous systems.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $118,700 - 218,600. 

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

#CyberDTP27

Qualifications:

We are seeking an AI Governance and Privacy Specialist who can operationalize responsible AI in real systems-especially agentic AI and LLM-enabled applications. This role blends governance and privacy expertise with enough software development fluency to create developer-ready guidance, implement controls-as-code patterns, and stand up measurable evaluation and monitoring workflows.

As a Senior Consultant, you will help clients and internal delivery teams move from AI principles to practices: risk tiering, model and agent inventories, technical guardrails, governance workflows integrated into the SDLC, and evidence artifacts suitable for audits and regulators.

Recruiting for this role ends on 6/5/2026.

Work You'll Do

You will lead and deliver AI governance, privacy, and security outcomes across the AI lifecycle, including:

  • Designing pragmatic AI governance operating models (intake, risk tiering, approvals, documentation standards, exception handling, and audit readiness) with a focus on GenAI and agentic AI deployments.
  • Building and maintaining AI system inventories (models, agents, tools, data sources, integrations), with clear ownership, intended use, risk classification, and change-control expectations.
  • Conducting AI risk assessments for privacy, security, model risk, and misuse-including prompt injection, sensitive data exposure, excessive agency, and overreliance-and translating findings into implementable mitigations.
  • Establishing technical control guidance for teams building agentic AI solutions: human-in-the-loop patterns, tool access controls, safe retrieval and grounding practices, logging/monitoring, token and data minimization, and incident response playbooks.
  • Implementing "governance in the workflow" by integrating governance checkpoints into product and engineering delivery (architecture reviews, release gates, evaluation requirements, documentation automation, and evidence capture).
  • Standing up or enhancing evaluation and monitoring approaches for GenAI systems: test plans, safety and quality metrics, red teaming workflows, and reporting dashboards for leaders and risk stakeholders.
  • Partnering cross-functionally with Cybersecurity, Privacy, Legal, Risk, Engineering, and Data Science to drive adoption and ensure governance guidance is usable, measurable, and repeatable.

The Team

You will join a cross-functional group working at the intersection of cyber, privacy, governance, and emerging AI delivery. The team helps organizations scale AI responsibly by combining governance and engineering patterns so teams can innovate faster without compromising trust.

Qualifications

Required

  • Bachelor's degree or equivalent practical experience.
  • 4+ years of experience in one or more of the following: AI governance, data privacy, security risk management, compliance and controls, AI product risk, model risk management, or technology risk consulting.
  • Demonstrated experience translating policies and regulatory expectations into operational workflows, artifacts, and controls (e.g., intake processes, inventories, decision logs, risk registers, RACI, playbooks).
  • Working knowledge of AI/ML/LLM systems and delivery lifecycles sufficient to assess real deployment risks and mitigations (training vs. RAG vs. fine-tuning vs. tool use, data dependencies, integration patterns).
  • Software development fluency: ability to collaborate with engineering teams on implementation details; ability to prototype or automate governance workflows in Python/SQL and to understand CI/CD and cloud deployment basics.
  • Practical experience with privacy program execution and artifacts (PIAs/DPIAs, vendor reviews, data inventories, data minimization, retention, and access control principles).
  • Ability to communicate clearly with both technical and non-technical stakeholders and produce executive-ready reporting.
  • Ability to travel 0-50%, on average, based on client and project needs.
  • Limited immigration sponsorship may be available.

Preferred

  • Previous consulting or Big 4 experience.
  • Hands-on experience operationalizing AI governance aligned to frameworks such as the NIST AI RMF and/or ISO/IEC 42001, with awareness of risk-based AI regulatory regimes (e.g., EU AI Act).
  • Experience with GenAI safety and evaluation practices (prompt injection testing, jailbreak resilience, hallucination measurement, toxicity/harm scoring, grounding effectiveness).
  • Familiarity with governance tooling and workflow platforms (e.g., OneTrust, GRC platforms, ticketing/workflow systems) and how to integrate them into engineering delivery.
  • Certifications such as CIPP/US, CIPM, IAPP AIGP, CISM, or CISSP.
  • Prior experience in cyber or enterprise security contexts (data security, identity, audit logging, secure SDLC).
  • Experience designing Human-in-the-Loop escalation pathways, exception handling, and automated safety protocols for highly autonomous systems.

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $118,700 - 218,600. 

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

#CyberDTP27

Education:Bachelor's DegreeEmployment Type:

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