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Credit Risk Modeler Jobs in Texas (NOW HIRING)

Develop and maintain credit risk models and metrics, including Potential Future Exposure (PFE), to support portfolio level and counterparty specific risk analysis and decision making. * Lead ...

Develop and maintain credit risk models and metrics, including Potential Future Exposure (PFE), to support portfolio level and counterparty specific risk analysis and decision making. * Lead ...

Develop and maintain credit risk models and metrics, including Potential Future Exposure (PFE), to support portfolio level and counterparty specific risk analysis and decision making. * Lead ...

Mines, models, analyzes large datasets, and utilizes predictive modeling techniques with an emphasis on optimizing credit risk and marketing campaign performance using the following predictive ...

Mines, models, analyzes large datasets, and utilizes predictive modeling techniques with an emphasis on optimizing credit risk and marketing campaign performance using the following predictive ...

Analyze forecasting models, debt rating models and ratings and execute remedial management action ... Credit Risk Job Family Group: Job Family: Time Type: Full time Primary Location: Irving Texas ...

Analyze forecasting models, debt rating models and ratings and execute remedial management action ... Credit Risk ----- Job Family Group: ----- Job Family: ----- Time Type: Full time ----- Primary ...

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Showing results 1-20

Credit Risk Modeler information

See Texas salary details

$112K

$130.5K

$168.6K

How much do credit risk modeler jobs pay per year?

As of Sep 10, 2026, the average yearly pay for credit risk modeler in Texas is $130,506.00, according to ZipRecruiter salary data. Most workers in this role earn between $119,200.00 and $133,600.00 per year, depending on experience, location, and employer.

What does a credit risk modeler do?

A Credit Risk Modeler is responsible for developing statistical models and analytical tools to assess the likelihood that borrowers will default on their loans or credit obligations. They use data analysis, statistical techniques, and machine learning algorithms to predict credit risk and help financial institutions make informed lending decisions. Their work involves gathering and cleaning data, building predictive models, validating model performance, and ensuring compliance with regulatory standards. Credit Risk Modelers play a crucial role in managing a bank's or lender's exposure to financial risk and maintaining a healthy loan portfolio.

What are the key skills and qualifications needed to thrive as a credit risk modeler?

To thrive as a Credit Risk Modeler, you need a solid background in quantitative finance, statistics, and data analysis, often supported by a degree in mathematics, finance, or a related field. Familiarity with programming languages such as Python, R, or SAS, as well as experience with risk modeling frameworks and regulatory requirements like Basel III, is typically required. Strong analytical thinking, attention to detail, and effective communication make a candidate stand out in this role. These skills are crucial for accurately predicting credit risk, ensuring regulatory compliance, and supporting informed decision-making in financial institutions.

How does a credit risk modeler typically collaborate with other departments within a financial institution?

Credit Risk Modelers frequently work alongside data scientists, underwriters, compliance teams, and business analysts to develop and refine risk assessment models. Collaboration with IT teams is common for implementing models into production systems, while regular interaction with regulatory and compliance groups ensures models meet legal standards. Effective communication with stakeholders is essential to translate technical findings into actionable business strategies, making cross-functional teamwork a key part of the role.

What is the difference between Credit Risk Modeler vs Credit Analyst?

AspectCredit Risk ModelerCredit Analyst
Required CredentialsBachelor's degree in finance, economics, or related field; often certifications like FRM or CFABachelor's degree in finance, accounting, or related field; certifications like CFA are common
Work EnvironmentQuantitative teams, risk management departments, financial institutionsBank branches, lending departments, credit departments
Employer & Industry UsageFinancial institutions, banks, credit agenciesBanks, lending companies, credit bureaus

The main difference is that Credit Risk Modelers develop statistical models to assess and predict credit risk, focusing on quantitative analysis. Credit Analysts evaluate individual creditworthiness of borrowers, primarily through financial statement analysis and credit reports. Both roles require financial knowledge, but Modelers are more data and model-focused, while Analysts are more client and credit evaluation-focused.

What are popular job titles related to Credit Risk Modeler jobs in TX?

For Credit Risk Modeler jobs in TX, the most frequently searched job titles are:

Infographic showing various Credit Risk Modeler job openings in Texas as of August 2026, with employment types broken down into 86% Full Time, and 14% Part Time. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $130,506 per year, or $62.7 per hour.

Sr. Credit Risk Governance Analyst

Addison, TX • On-site

Other

Posted 14 days ago


Key responsibilities

  • Provide second-line oversight of the end-to-end credit decisioning process to ensure compliance with policies, risk appetite, and regulatory standards.

  • Execute credit policy testing and control reviews to identify breaches, control gaps, and emerging risks, and recommend remediation actions.

  • Develop and maintain governance reporting, dashboards, and documentation to communicate credit risk themes, testing results, and remediation progress.


Job description

Job Description: General Summary The Sr. Credit Risk Governance Analyst is responsible for supporting and strengthening the organization’s credit risk governance framework through independent oversight of credit decisioning, credit policy management and testing, credit risk process governance, retrospective credit reviews, and second-line model risk challenge activities.

This role partners with Credit Risk, Enterprise Risk Management, Compliance, Legal, Analytics, Operations, Technology, and vendor partners to assess whether credit strategies, policies, models, procedures, controls, and approval authorities are operating as intended and aligned with risk appetite, regulatory expectations, and internal governance standards.

The position develops governance reporting, identifies control gaps and emerging risk trends, supports issue escalation and remediation, maintains process documentation and SOP governance routines, and helps mature the credit risk control environment through durable, auditable, and consistently applied governance practices.

Principal Duties and Responsibilities
  • Provide second-line oversight of the end-to-end credit decisioning process to assess alignment with approved credit policy, risk appetite, delegated authorities, governance standards, and applicable regulatory expectations.
  • Execute credit policy testing and control reviews to validate consistent policy application, identify breaches, exceptions, control gaps, and emerging risk trends, and recommend remediation actions.
  • Maintain and support the credit policy framework, including policy inventory, approval workflows, exception monitoring, periodic review routines, version control, and documentation of policy changes.
  • Provide independent challenge to credit risk models, strategies, scorecards, decision rules, assumptions, performance monitoring, and model governance documentation in coordination with Model Risk Management and Analytics.
  • Support model risk oversight by reviewing model performance results, validation findings, monitoring thresholds, implementation controls, issue remediation, and adherence to model risk management standards.
  • Perform retrospective credit risk reviews to evaluate decision quality, policy adherence, adverse trends, override activity, exception activity, customer outcomes, and root causes of credit performance or control issues.
  • Develop and maintain credit risk standard operating procedures, process maps, control inventories, governance documentation, job aids, and review routines to support consistent execution and audit readiness.
  • Development and maintenance of credit risk and collections process documentation, including process maps, policies, SOPs, RACI matrices, FMEAs, and other governance and operational documentation as needed.
  • Support credit risk SOP governance by coordinating periodic reviews, identifying missing or outdated procedures, promoting consistent documentation standards, and tracking remediation of procedure gaps.
  • Analyze governance results, credit decisioning trends, policy exceptions, model monitoring outputs, control gaps, and issue data to identify risks, root causes, and opportunities to strengthen the credit risk control environment.
  • Prepare governance reporting, dashboards, committee materials, risk summaries, and executive-level updates that communicate credit risk themes, testing results, model oversight observations, and remediation progress.
  • Escalate material credit governance concerns, policy breaches, model risk observations, control weaknesses, or recurring process issues to appropriate governance forums and leadership stakeholders.
  • Support audits, examinations, compliance reviews, model risk reviews, issue management activities, and governance inquiries by providing documentation, analysis, control evidence, and process explanations.
  • Monitor regulatory, business, product, and credit strategy changes to assess impacts to credit policies, decisioning controls, model governance, procedures, reporting, and oversight routines.
  • Perform additional credit governance, enterprise risk management, and special project duties as assigned.
Experience and Education

Bachelor's degree in business, finance, economics, risk management, data analytics, or a related field required; Master's degree or risk-related certification preferred. 5+ years of experience in financial services, credit risk, enterprise risk management, model risk management, compliance, audit, governance, analytics, or related risk oversight functions. Experience with credit policy management, credit decisioning, credit risk controls, model governance, policy testing, process management, issue management, or second-line oversight is preferred.

Required Skills, Abilities, Soft Skill Factors

Strong understanding of credit risk management, credit decisioning strategies, credit policy governance, risk appetite, controls, and financial services regulatory expectations. Knowledge of model risk management concepts, including model validation, performance monitoring, assumptions, thresholds, implementation controls, and independent challenge practices. Ability to execute policy testing, control reviews, retrospective reviews, root cause analysis, and governance assessments with accuracy, consistency, and appropriate documentation. Strong quantitative, analytical, problem-solving, and critical thinking skills with the ability to identify trends, synthesize data, and translate findings into clear governance recommendations. Strong process mapping, procedure development, control documentation, and issue tracking skills, with an emphasis on durable, auditable governance routines. Effective written and verbal communication skills, including the ability to prepare executive-ready summaries, committee materials, risk reporting, testing results, and remediation updates. Ability to work independently as a senior individual contributor, manage multiple priorities, meet deadlines, and influence cross-functional partners without direct authority. High attention to detail, sound judgment, professional skepticism, and ability to challenge assumptions while maintaining productive stakeholder relationships. Proficiency with Microsoft Office applications and familiarity with reporting, analytics, workflow, model monitoring, or governance tools is preferred.

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