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Model Risk Jobs in North Carolina (NOW HIRING)

Position Overview: Assist in the development, implementation, and maintenance of the Model Risk Management (MRM) program within SECU through the development and validation of statistical models ...

New

Essential Responsibilities: * (30%) Development and execution of policies, standards, and internal procedures for all phases of the model and AI life cycle, including identification, risk assessment ...

New

The Model Risk APM is primarily responsible for completing audit engagements with minimal supervision from managers. The APM is expected to execute audit engagements against plan and schedule ...

Audit Project Manager - Model Risk

Charlotte, NC · On-site

$101K - $133K/yr

This Audit Project Manager position supports the Model Risk team within Corporate Audit Services. This role is primarily responsible for managing and executing the administrative aspects of ...

Work closely within the Risk organization to validate accuracy and performance of all models, whether statistical/AI/ML or non-statistical to identify any issues requiring further investigation, and ...

The role partners closely with Second Line of Defense (2LOD) teams (Enterprise Risk Management, Model Risk Management, Compliance, Law Division, and Technology Risk Oversight) to ensure emerging AI ...

Evaluates model risk control strengths around model development, implementation, and use as it pertains to elements of model conceptual soundness, modeling methodology, model limitations, data ...

Experience in Model Risk. * Experience in AI Governance. Compensation range: The salary range for this position is: $143,320 - $273,930 . USAA does not provide visa sponsorship for this role. Please ...

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Model Risk information

See North Carolina salary details

$13

$27

$67

How much do model risk jobs pay per hour?

As of Jun 14, 2026, the average hourly pay for model risk in North Carolina is $27.57, according to ZipRecruiter salary data. Most workers in this role earn between $17.69 and $35.19 per hour, depending on experience, location, and employer.

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 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 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 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 are the most commonly searched types of Model Risk jobs in North Carolina? The most popular types of Model Risk jobs in North Carolina are:
What job categories do people searching Model Risk jobs in North Carolina look for? The top searched job categories for Model Risk jobs in North Carolina are:
Infographic showing various Model Risk job openings in North Carolina as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $57,345 per year, or $27.6 per hour.

Model Risk Analyst

NC SECU

Raleigh, NC • Hybrid

Full-time

Posted 2 days ago


Job description

If you are motivated and believe in the credit union philosophy of "People Helping People," join our team!

Position Overview:

Assist in the development, implementation, and maintenance of the Model Risk Management (MRM) program within SECU through the development and validation of statistical models, qualitative models, and models developed with other quantitative algorithms.

Essential Responsibilities:

  • (40%) Execute model validation activities across the model life-cycle including model validations, ongoing performance evaluation, and tracking model findings to ensure models across SECU are conceptually sound relative to their intended use and performing appropriately. Execute end-to-end testing plans for validation and review of SECU's statistical and qualitative models with oversight and guidance from supervisor and other senior validation staff.
  • (30%) Validate the performance and controls of statistical models using provided model development documentation and communications with model developers. Document and present findings to management and model owners.
  • (10%) Provide input for enhancements to the model risk management framework, including maintaining model inventory and model risk rankings.
  • (10%) Develop and maintain effective partnerships within SECU, particularly with model owners, model developers and data analysts.
  • (10%) Assist in implementation of, and adherence to, the MRM Policy and associated model risk SOPs across SECU.

Required Education & Experience (Knowledge, Skills, & Abilities):

  • Bachelors in a quantitative discipline (Economics, statistics, finance, data science or analytics, math, physics, or related field)
  • 3+ years of experience in modeling or analytics
  • Ability to assess model conceptual design, backtesting of model results, assumptions, controls over data flows, model execution, and compliance of model results with intended application by model users.
  • Advanced programming skills in a statistical programming language, such as SAS, R, or Python. Ability to write computer code to perform analysis on complex modeling and analytical challenges and to review code written by others for accuracy and efficiency, with minimal guidance from supervisor.
  • Academic and/or professional understanding of advanced mathematical and statistical modeling techniques, including logistic regression, time series analysis, linear regression, Monte Carlo simulation, Artificial Intelligence/Machine Learning (AI/ML) techniques, etc.
  • Demonstrated ability to contribute to multiple projects simultaneously under guidance from supervisor.
  • Strong oral and written communication skills. Experience contributing to detailed technical validation reports and/or model development documentation.
  • Strong attention to detail and the ability to understand and analyze complex modeling and analytical challenges with some guidance from supervisor and senior staff.
  • Perform job functions independently with some day-to-day oversight from supervisor.

Preferred Education & Experience (Knowledge, Skills, & Abilities):

  • Masters in quantitative discipline
  • Experience in financial services or consulting industry
  • Experience developing or validating models used for CECL, Credit Risk, CCAR/Stress Testing, PPNR, ALM, loan pricing and/or mortgage servicing rights, derivatives, Compliance (BSA/AML/OFAC), Liquidity, or Fraud
  • Subject matter expertise in generative large language models (Artificial Intelligence)

Job Environment & Physical Requirements:

  • Hybrid expectations
  • Sitting for prolonged periods
  • Computer for prolonged periods

SECU provides equal employment opportunity to all qualified persons regardless of race, color, religion, age, sex, sexual orientation, gender identity, national origin, genetic information, disability, veteran status, or other classification protected by law.

Disclaimer

State Employees' Credit Union reserves the right to fill this role at a higher/lower level based on business need.