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Model Risk Jobs in Florida (NOW HIRING)

Develop risk statements, mitigation plans, and quantitative risk models * Support and participate in trade studies, decision tree development, and product review meetings * Present detailed risk ...

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

Actuary - Auto and Property Modeling

Tampa, FL · On-site +1

$110.10K - $129.50K/yr

Knowledge of Model Risk Management, Model Governance, and Regulatory requirements. * US military experience through military service or a military spouse/domestic partner. Compensation range: The ...

Actuary - Auto and Property Modeling

Tampa, FL · On-site +1

$110.10K - $129.50K/yr

Knowledge of Model Risk Management, Model Governance, and Regulatory requirements. * US military experience through military service or a military spouse/domestic partner. Compensation range: The ...

... cost modeling, risk management, and financial analyses for 60Hz Long-Term Program (LTP) and ... Operations & Maintenance (O&M) projects across North and Latin America. Your work directly supports ...

Participate in the oversight of model governance including the validation of model assumptions and results * Assist in formation of risk appetite statements and monitoring of compliance * Identify ...

Participate in the oversight of model governance including the validation of model assumptions and results * Assist in formation of risk appetite statements and monitoring of compliance * Identify ...

Participate in the oversight of model governance including the validation of model assumptions and results * Assist in formation of risk appetite statements and monitoring of compliance * Identify ...

Produce forecasting models, analysis, and recommendations to understand and mitigate risk potential vulnerabilities * Analyse and proactively identify emerging risk trends and adapt existing ...

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Showing results 1-20

Model Risk information

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

To thrive as a Model Risk Analyst, you need a solid background in quantitative analysis, statistics, or finance, often supported by an advanced degree in a related field. Familiarity with model validation tools, programming languages such as Python or R, and regulatory frameworks like SR 11-7 is essential. Strong analytical thinking, attention to detail, and effective communication skills are crucial for evaluating models and presenting findings to stakeholders. These skills ensure model integrity, regulatory compliance, and risk mitigation in financial institutions.

What are some typical challenges faced by professionals working in Model Risk, and how can they be addressed?

Professionals in Model Risk often encounter challenges such as ensuring model accuracy, managing regulatory compliance, and effectively communicating complex technical findings to non-technical stakeholders. Addressing these challenges requires a strong understanding of both quantitative modeling and relevant regulations, as well as strong collaboration skills to work with model developers, auditors, and business units. Staying informed about evolving regulatory standards and participating in ongoing training can also help model risk professionals remain effective and add value to their organizations.

What is model risk?

Model risk refers to the potential for adverse consequences resulting from decisions based on incorrect or misused models. In financial institutions, model risk can arise if a model's assumptions are flawed, if the data input is poor, or if the model is applied inappropriately. Managing model risk involves validating models, monitoring their performance, and ensuring that they are used within their intended scope. Effective model risk management helps organizations avoid significant financial losses and comply with regulatory requirements.

What is the difference between Model Risk vs Model Validation?

AspectModel RiskModel Validation
Primary FocusIdentifying, assessing, and mitigating risks associated with modelsEvaluating and testing models to ensure accuracy and reliability
Required CredentialsQuantitative skills, risk management certifications, industry experienceQuantitative expertise, validation certifications, industry knowledge
Work EnvironmentRisk management teams within financial institutions or firmsModel validation teams, often within risk or model development departments
Industry UsageUsed across banking, insurance, and investment firms to manage model-related risksCommonly employed in financial services to verify model performance

Model Risk focuses on managing the potential negative impacts of models, including errors and misuse, while Model Validation concentrates on testing and confirming the accuracy and robustness of models. Both roles are essential in financial industries to ensure models are reliable and risks are minimized.

What are the most commonly searched types of Model Risk jobs in Florida? The most popular types of Model Risk jobs in Florida are:
What cities in Florida are hiring for Model Risk jobs? Cities in Florida with the most Model Risk job openings:
Senior Associate, National Security-Cyber Security Governance

Senior Associate, National Security-Cyber Security Governance

Alvarez and Marsal

Miami, FL

$95.60K - $123.40K/yr

Full-time

Medical, Life, Retirement, PTO

Posted 26 days ago


Job description

Description

About Alvarez & Marsal

Alvarez & Marsal (A&M) is a global consulting firm with over 10,000 entrepreneurial, action and results-oriented professionals in over 40 countries. We take a hands-on approach to solving our clients' problems and assisting them in reaching their potential. Our culture celebrates independent thinkers and doers who positively impact our clients and shape our industry. The collaborative environment and engaging work—guided by A&M's core values of Integrity, Quality, Objectivity, Fun, Personal Reward, and Inclusive Diversity—are why our people love working at A&M.

The team

At A&M you will have the opportunity to work with a diverse team of supportive and motivated professionals that love to share their knowledge and depth of industry experience with others. A&M's Disputes and Investigations practice comprises professionals from a wide range of backgrounds, who bring and share their deep expertise in conducting investigations and delivering expert witness reports. We have an inclusive developmental environment where everyone has the opportunity to learn and grow. Our culture is characterized by openness and entrepreneurial thinking, with a foundation of mutual respect and high-quality standards for our work. We strive to remove bureaucracy in favor of recognizing effort and results through advancement opportunities and a motivating performance-based reward structure.

How you will contribute

With the rapid adoption of AI technologies and evolving regulatory landscape, demand for AI-focused security analysis and compliance expertise is growing exponentially. Our team supports organizations, investors and counsel in identifying, assessing, and mitigating risks associated with AI system deployment, algorithmic bias, data privacy, and model security. We focus on implementing secure AI/ML pipelines, establishing AI governance frameworks, conducting model risk assessments, and ensuring compliance with emerging AI regulations. Our approach integrates traditional cybersecurity with AI-specific security controls, leveraging automated testing, model monitoring, and adversarial robustness techniques. The team serves as trusted advisors to organizations navigating AI regulatory requirements, security certifications, and responsible AI implementation.

Responsibilities:

· Lead technical teams in executing AI security assessments, model audits, and compliance reviews related to AI Act (EU), NIST AI Risk Management Framework, ISO/IEC 23053/23894, and emerging AI governance standards. Develop AI risk assessment methodologies and implement continuous monitoring solutions for production ML systems.

· Design and implement secure AI/ML architectures incorporating MLOps security practices, including model versioning, data lineage tracking, feature store security, and secure model deployment pipelines. Integrate security controls for Large Language Models (LLMs), including prompt injection prevention, output filtering, and embedding security.

· Conduct technical assessments of AI/ML systems using tools such as:

· AI Security Tools: Adversarial Robustness Toolbox (ART), Foolbox, CleverHans for adversarial testing

· MLOps Platforms: MLflow, Kubeflow, Amazon SageMaker, Azure ML, Google Vertex AI

· Model Monitoring: Evidently AI, Fiddler AI, WhyLabs, Neptune.ai for drift detection and explainability

· LLM Security: Guardrails AI, NeMo Guardrails, LangChain security modules, OWASP LLM Top 10 tools

· Privacy-Preserving ML: PySyft, TensorFlow Privacy, Opacus for differential privacy implementation

· Implement AI compliance and governance solutions addressing:

· Regulatory Frameworks: EU AI Act, Canada's AIDA, US AI Executive Orders, Singapore's Model AI Governance Framework

· Industry Standards: ISO/IEC 23053, ISO/IEC 23894, IEEE 7000 series, NIST AI RMF

· Sector-Specific Requirements: FDA AI/ML medical device regulations, GDPR Article 22 (automated decision-making), SR 11-7 model risk management

· Develop and execute penetration testing specifically for AI systems, including:

· Model extraction attacks and defenses

· Data poisoning vulnerability assessments

· Membership inference and model inversion testing

· Prompt injection and jailbreaking assessments for LLMs

· Backdoor detection in neural networks

· Program and deploy custom security solutions using:

· Languages: Python (PyTorch, TensorFlow, scikit-learn), R, Julia

· AI Frameworks: Hugging Face Transformers, LangChain, LlamaIndex, AutoML tools

· Security Libraries: SHAP, LIME for explainability; Fairlearn, AIF360 for bias detection

· Infrastructure: Docker, Kubernetes, Terraform for secure AI deployment

· Integrate AI security with traditional security frameworks including Zero Trust architecture, IAM solutions, and SIEM platforms. Implement automated compliance monitoring using AI-powered security orchestration tools (SOAR platforms like Splunk Phantom, Palo Alto Cortex XSOAR).

· Assess and mitigate risks in:

· Foundation models and transfer learning implementations

· Federated learning systems

· Edge AI deployments

· Multi-modal AI systems

· Generative AI applications (GPT, DALL-E, Stable Diffusion implementations)

· Create technical documentation including AI system security architecture reviews, threat models specific to ML pipelines, compliance mappings, and remediation roadmaps aligned with both traditional security standards (NIST 800-53, ISO 27001) and AI-specific frameworks.

· Availability for up to 15% travel required to client sites and assessment locations.

Qualifications:

· 3+ years of experience in AI/ML development, deployment, or security assessment

· 2+ years of experience in information security, with focus on application security or cloud security

· Hands-on experience with AI/ML frameworks (TensorFlow, PyTorch, scikit-learn, Hugging Face)

· Proficiency in Python programming with experience in AI/ML libraries and security testing tools

· Experience with cloud AI platforms (AWS SageMaker, Azure ML, Google Vertex AI, Databricks)

· Knowledge of AI compliance frameworks: NIST AI RMF, EU AI Act requirements, ISO/IEC 23053/23894

· Experience with MLOps tools and secure model deployment practices

· Understanding of adversarial machine learning and AI security threats (OWASP ML Top 10, ATLAS framework)

· Familiarity with privacy-preserving ML techniques (differential privacy, federated learning, homomorphic encryption basics)

· Experience with containerization (Docker, Kubernetes) and infrastructure as code

· Knowledge of traditional security frameworks (NIST CSF, NIST 800-53, ISO 27001)

· Ability to obtain a USG security clearance

Preferred Certifications:

· One or more AI/ML certifications: AWS Certified Machine Learning, Google Cloud Professional ML Engineer, Azure AI Engineer

· Security certifications: CISSP, CCSP, CompTIA Security+, CEH

· Specialized: GIAC AI Security Essentials (GAISE), Certified AI Auditor (when available)

Your journey at A&M

We recognize that our people are the driving force behind our success, which is why we prioritize an employee experience that fosters each person’s unique professional and personal development. Our robust performance development process promotes continuous learning, rewards your contributions, and fosters a culture of meritocracy. With top-notch training and on-the-job learning opportunities, you can acquire new skills and advance your career.

We prioritize your well-being, providing benefits and resources to support you on your personal journey. Our people consistently highlight the growth opportunities, our unique, entrepreneurial culture, and the fun we have together as their favorite aspects of working at A&M. The possibilities are endless for high-performing and passionate professionals.

Regular employees working 30 or more hours per week are also entitled to participate in Alvarez & Marsal Holdings’ fringe benefits consisting of healthcare plans, flexible spending and savings accounts, life, AD&D, and disability coverages at rates determined periodically as well as a 401(k) retirement savings plan. Provided the eligibility requirements are met, employees will also receive an annual discretionary contribution to their 401(k) retirement savings plan from Alvarez & Marsal. Additionally, employees are eligible for paid time off including vacation, personal days, seventy-two (72) hours of sick time (prorated for part time employees), ten federal holidays, one floating holiday, and parental leave. The amount of vacation and personal days available varies based on tenure and role type. Click here for more information regarding A&M’s benefits programs

The salary range is $80,000 - $110,000 annually, dependent on several variables including but not limited to education, experience, skills, and geography. In addition, A&M offers a discretionary bonus program which is based on a number of factors, including individual and firm performance. Please ask your recruiter for details.

Alvarez & Marsal recruits on an ongoing basis. Candidates are considered as they apply, until the opportunity is filled. Candidates are encouraged to apply expeditiously to any role(s) that they are qualified for and that are of interest to them.

A&M does not require or administer lie detector tests as a condition of employment or continued employment. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

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