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Model Risk Management Jobs in Florida (NOW HIRING)

MHI

Leader, Fleet Risk Management

Lake Mary, FL · On-site

Fleet Risk Manager Company Overview At Mitsubishi Power, we're not just building better clean ... Strong analytical, modeling, and technical interpretation skills. * Proficient with MS Office; SAP ...

Emigrant Bank

Senior Risk Manager

Miami, FL · On-site

Risk Management Reports To: Chief Risk Officer Employment Status: Full-Time, Exempt Office Location ... Participate in the oversight of model governance including the validation of model assumptions and ...

Emigrant Bank

Senior Risk Manager

Miami, FL

Risk Management Reports To: Chief Risk Officer Employment Status: Full-Time, Exempt Office Location ... Participate in the oversight of model governance including the validation of model assumptions and ...

Emigrant Bank

Senior Risk Manager

Miami, FL

Risk Management Reports To: Chief Risk Officer Employment Status: Full-Time, Exempt Office Location ... Participate in the oversight of model governance including the validation of model assumptions and ...

Deloitte

Financial Risk Manager

Miami, FL

Credit Risk, Liquidity Risk, Market Risk, Capital Management/Stress Testing * Knowledge of financial services business models, products, and services * Experience in banking, digital assets, or ...

Ankura

Model Validation Director

Tampa, FL · On-site +1

Build, enhance or localize model risk management programs including coverage assessments, change management, access management procedures, internal controls, and transaction monitoring and watchlist ...

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Model Risk Management information

See Florida salary details

$27.3K

$61.5K

$103.1K

How much do model risk management jobs pay per year?

As of May 29, 2026, the average yearly pay for model risk management in Florida is $61,524.00, according to ZipRecruiter salary data. Most workers in this role earn between $46,700.00 and $67,600.00 per year, depending on experience, location, and employer.

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 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.
More about Model Risk Management jobs
What are the most commonly searched types of Model Risk Management jobs in Florida? The most popular types of Model Risk Management jobs in Florida are:
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What cities in Florida are hiring for Model Risk Management jobs? Cities in Florida with the most Model Risk Management job openings:
Model Risk Management jobs near you
Infographic showing various Model Risk Management job openings in Florida as of May 2026, with employment types broken down into 96% Full Time, and 4% Contract. Highlights an 87% In-person, 9% Hybrid, and 4% Remote job distribution, with an average salary of $61,524 per year, or $29.6 per hour.
Director, AI Enablement & Governance

Director, AI Enablement & Governance

Life Extension Foundation Buyers Club Inc

Fort Lauderdale, FL • On-site

$222K - $232.50K/yr

Full-time

Posted yesterday

Job description

The Director of AI Enablement & Governance leads the responsible adoption, scaling, and oversight of artificial intelligence across the organization. This role sits at the intersection of technology, risk, compliance, and business transformation and is tasked with defining and operationalizing AI governance frameworks, enabling business units to deploy AI solutions effectively, and ensuring alignment with regulatory, ethical, and security standards. This leadership position combines deep knowledge of AI/ML with policy development and cross-functional collaboration skills.

Core Duties and Responsibilities:

  • Develop and execute the enterprise AI enablement strategy aligned with business objectives.
  • Partner with business leaders to identify, prioritize, and scale high-impact AI use cases.
  • Establish reusable frameworks, tools, and best practices to accelerate AI adoption.
  • Build and lead internal AI communities of practice to drive knowledge sharing and innovation.
  • Oversee AI solution lifecycle from ideation through deployment and monitoring.
  • Design and implement a comprehensive AI governance framework covering model risk, ethics, privacy, and compliance.
  • Define policies and standards for responsible AI use, including fairness, transparency, and accountability.
  • Establish model validation, monitoring, and audit processes.
  • Ensure compliance with evolving AI regulations (e.g., EU AI Act, U.S. regulatory guidance) and internal policies.
  • Partner with Legal and Security teams to manage AI-related risks and ensure compliance.
  • Collaborate with data teams to ensure high-quality, secure, and compliant data usage.
  • Define standards for model documentation, explainability, and reproducibility.
  • Implement processes for model performance tracking, drift detection, and retraining.
  • Ensure proper governance over third-party AI tools and vendors.
  • Build, mentor, and lead a high-performing AI governance and enablement team.
  • Serve as a trusted advisor to senior leadership on AI opportunities and risks.
  • Drive change management efforts to embed responsible AI practices across the organization.
  • Deliver training and awareness programs on AI governance and ethical use.
  • Evaluate and select AI platforms, tools, and vendors aligned with governance standards.
  • Oversee implementation of AI governance tooling (e.g., model registries, monitoring systems).
  • Ensure integration of governance controls into MLOps and data pipelines.
  • 2 onsite days per week is an essential function of this position
  • Additional duties as needed


Position Requirements:

  • Bachelor’s degree in Computer Science, Data Science, Engineering, or related field (Master’s preferred).
  • 10+ years of experience in AI/ML, data science, or related domains, with leadership experience.
  • Proven experience developing and implementing AI governance frameworks.
  • Strong understanding of machine learning lifecycle, model risk management, and data governance.
  • Familiarity with AI regulations, ethical frameworks, and industry standards.
  • Experience working cross-functionally with technical and non-technical stakeholders.
  • Experience in regulated industries preferred (e.g., finance, healthcare, insurance).
  • Knowledge of frameworks such as NIST AI Risk Management Framework, ISO/IEC AI standards.
  • Experience with MLOps platforms, model monitoring tools, and AI lifecycle management.
  • Strong communication skills with the ability to influence executive stakeholders.