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Model Risk Jobs in Utah (NOW HIRING)

SoFi

Fraud Model Analyst

Cottonwood Heights, UT

This individual will partner closely with Model Risk Management (MRM), Legal, Compliance, Fraud Strategy, and external vendors to support onboarding, validation, and ongoing monitoring of vendor ...

SoFi

Fraud Model Analyst

Cottonwood Heights, UT · On-site

This individual will partner closely with Model Risk Management (MRM), Legal, Compliance, Fraud Strategy, and external vendors to support onboarding, validation, and ongoing monitoring of vendor ...

Wsgr

Senior AI Risk Advisor

Salt Lake City, UT · On-site +1

$163.20K - $220.80K/yr

Lead AI risk assessments across the full model lifecycle - evaluating third-party AI vendors, foundation models, and AI-powered platforms for data privacy risks, model behavior, security posture, and ...

Medallion Bank

Credit Risk Manager

Salt Lake City, UT · Hybrid

Partner with Data Analytics and Finance teams on data acquisition, model validation support ... Minimum5years of experience in credit risk, financial analytics, or a related quantitative role ...

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$13

$27

$67

How much do model risk jobs pay per hour?

As of May 30, 2026, the average hourly pay for model risk in Utah is $27.62, according to ZipRecruiter salary data. Most workers in this role earn between $17.74 and $35.24 per hour, depending on experience, location, and employer.

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 popular job titles related to Model Risk jobs in Utah? For Model Risk jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Model Risk jobs in Utah look for? The top searched job categories for Model Risk jobs in Utah are:
Model Risk jobs near you
Model Validation Analyst

Model Validation Analyst

First Electronic Bank

Salt Lake City, UT • On-site

Full-time

Posted 8 days ago

Job description

Job Type
Full-time
Description
At First Electronic Bank (FEB), we are driven by the purpose to make credit accessible to everyday Americans, and their businesses. Partnering with some of the most innovative FinTech companies in the nation, we offer a wide range of consumer and commercial credit products on a national basis. Offering revolving lines of credit, private-label credit cards, installment financing programs and more, FEB's engages with strategic, collaborative partnerships, promoting services and products to provide the most beneficial consumer and commercial financing solutions.
The Model Validation Analyst plays a critical role in ensuring model integrity, regulatory compliance, and sound risk management practices. This role reports to the Head of Credit Risk and Portfolio Analytics Credit and supports the Bank's strategic partner program by reviewing statistical models used in underwriting and assessing overall model risk across partnerships.
What You'll Do:
  • Review third-party model validation documentation for conceptual soundness and alignment with applicable regulatory guidance.
  • Assess and challenge credit models and underwriting strategies used in loan origination.
  • Maintain a comprehensive inventory of all models used by the Bank, including underwriting, fraud, and marketing models.
  • Evaluate model performance monitoring practices and ensure appropriate tracking of key risk indicators.
  • Partner with Compliance, Legal, and Strategic Partner Management teams to ensure models meet applicable regulatory and internal policy requirements.
  • Prepare reports and present model risk metrics to the Bank's Credit Committee.
  • Monitor and test credit origination strategies to validate accuracy and consistency of credit decisions.
  • Conduct model and credit risk due diligence for prospective fintech partners.
  • Participate in or lead initiatives to enhance model risk management processes and improve overall risk oversight.

Requirements
What We're Looking For:
Education & Experience
  • Master's degree in Statistics, Data Science, Computer Science, Economics, Mathematics, or a related quantitative field;
  • OR Bachelor's degree with 3+ years of relevant experience in model development or validation.
  • Prior experience developing and/or validating credit risk models is required.
  • 3+ years of experience in banking, financial services, or a related industry is preferred.

Technical Skills
  • Strong understanding of statistical modeling techniques, including regression and classification models.
  • Ability to evaluate model structure, assumptions, and validation methodologies.
  • Familiarity with machine learning models and their application in credit decisioning.
  • Proficiency in one or more programming languages/tools, such as SQL, Python, R, or SAS.
  • Working knowledge of credit policies and underwriting frameworks.
  • Familiarity with CECL models is a strong plus.

Professional Skills
  • Ability to work effectively across cross-functional teams, including Compliance, Audit, and Model Risk Management.
  • Strong analytical and critical thinking skills with attention to detail.
  • Effective written and verbal communication skills, including the ability to present technical concepts to non-technical audiences.
  • Strong organizational and prioritization skills in a fast-paced environment.

Additional Information
  • Experience working with regulatory, audit, or model risk management frameworks is a plus.
  • Proficiency in Microsoft Office Suite (Excel, Word, PowerPoint, Outlook) required.

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