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Contract Model Risk Governance Jobs in Missouri (NOW HIRING)

Yantran LLC

Data Governance Engineer

Saint Louis, MO · On-site

Data lineage, metadata models, business glossary, classification Identity/RBAC alignment for ... Metadata Management, Data Quality Governance Data Contracts * Build and maintain standards: Naming ...

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Contract Model Risk Governance information

What are some common challenges faced by professionals in Contract Model Risk Governance roles, and how can they be addressed?

Professionals in Contract Model Risk Governance often encounter challenges such as keeping up with evolving regulatory requirements, ensuring thorough model documentation, and effectively communicating risk findings to both technical and non-technical stakeholders. Balancing the need for detailed model validation with tight project timelines can also be demanding. To address these challenges, it's important to foster strong cross-functional collaboration, stay updated on industry best practices, and develop clear communication strategies for reporting risk and compliance issues.

What is the difference between Contract Model Risk Governance vs Contract Model Validation?

AspectContract Model Risk GovernanceContract Model Validation
Primary FocusOverseeing and managing risks associated with contract models, ensuring compliance and risk mitigationAssessing and testing contract models to ensure accuracy and reliability
ResponsibilitiesEstablishing policies, monitoring risk exposure, and implementing controlsPerforming independent reviews, testing model assumptions, and validating outputs
Work EnvironmentRisk management teams, compliance departments, regulatory interactionsQuantitative teams, model validation units, audit functions

While Contract Model Risk Governance focuses on managing and overseeing risks related to contract models, Contract Model Validation involves the technical assessment and testing of those models to ensure their accuracy and reliability. Both roles are essential in a comprehensive risk management framework within financial institutions and industries relying on contract models.

What are the key skills and qualifications needed to thrive in Contract Model Risk Governance, and why are they important?

To excel in Contract Model Risk Governance, you need a strong background in risk management, quantitative analysis, and familiarity with regulatory requirements, often supported by a degree in finance, mathematics, or a related field. Proficiency with risk management software, model validation tools, and knowledge of frameworks such as SR 11-7 is typically required. Attention to detail, critical thinking, and effective communication are crucial soft skills for evaluating model risk and collaborating with stakeholders. These skills ensure robust oversight of model risk, regulatory compliance, and support sound decision-making within financial institutions.

What is Contract Model Risk Governance?

Contract Model Risk Governance refers to the framework and processes used by organizations to identify, assess, monitor, and mitigate risks associated with the use of models in contracts or contractual obligations. This role ensures that the use of quantitative models in financial and business contracts complies with regulatory standards and internal policies, reducing the likelihood of errors, misinterpretations, or financial losses. Professionals in this field often oversee model validation, implementation, and documentation, and work closely with compliance, risk, and legal teams. Effective governance helps maintain model integrity and supports sound decision-making across the organization.
What are the most commonly searched types of Model Risk Governance jobs in Missouri? The most popular types of Model Risk Governance jobs in Missouri are:
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Contract Model Risk Governance jobs near you
Infographic showing various Contract Model Risk Governance job openings in Missouri as of June 2026, with employment types broken down into 1% As Needed, 87% Full Time, 11% Part Time, and 1% Contract. Highlights an 79% Physical, 3% Hybrid, and 18% Remote job distribution.

Senior Credit Risk/Decision Scientist

TBO Bank

Kansas City, MO

Full-time

Posted 29 days ago

Job description

POSITION DESCRIPTION

Title: Senior Credit Risk/Decision Scientist

Classification: Salaried, exempt

Position Type: Full Time

Reports to: Credit Risk Officer – Digital Banking

Location: TBD

Summary/Objective

The Senior Credit Risk/Decision Scientist will be responsible for quantitative model development, credit strategy design, and analytical decision support throughout the customer life cycle. This role will build, validate, and monitor predictive models; design and interpret strategy tests; and translate analytical findings into actionable credit policy.

Essential Functions

Duties/Responsibilities:

• Develop, validate, and recalibrate credit risk scorecards and predictive models for acquisition, account management, and loss forecasting.

• Design and analyze champion-challenger tests to optimize credit policy and decisioning thresholds.

• Partner with Marketing to enhance response and bidding models focused on improved conversion and acquisition cost

• Monitor model performance through ongoing back-testing, stability analysis, and drift detection; recommend recalibration as needed.

• Integrate and evaluate third-party data vendors to enhance model features, leads waterfall and risk segmentation.

• Support prescreen modeling and strategies in partnership with marketing and credit strategy teams.

• Conduct portfolio-level risk analysis including delinquency trending, vintage analysis, and loss projections.

• Collaborate with compliance on model risk governance, fair lending review, and SR 11-7 documentation requirements.

• Prepare clear model documentation, validation reports, and executive-ready presentations for internal stakeholders and regulators.

• Partner with IT and data engineering teams on data pipelines, feature engineering, and model deployment in production environments.

• Contribute to fraud detection and collections analytics as workflow allows, supporting cross-functional risk initiatives.

Competencies:

• 5+ years of experience in credit risk modeling, decision science, or quantitative analytics within a bank, credit union, fintech, or consumer lender.

• Demonstrated experience building and validating scorecards using logistic regression, decision trees, gradient boosting, or similar techniques.

• Strong proficiency in Python or R for statistical modeling, data manipulation, and visualization

• Solid SQL skills; ability to independently access and analyze large datasets

• Familiarity with credit bureau data (Experian, Equifax, TransUnion) and alternative data sources.

• Understanding of model risk management frameworks, including SR 11-7 / OCC 2011-12 guidance.

• Strong analytical communication skills — ability to translate complex model outputs into actionable business recommendations.

• Bachelor's degree in Statistics, Mathematics, Economics, Computer Science, Finance, or a related quantitative field.

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