ZipRecruiter

Log In

1

Credit Risk Developer Jobs in Missouri (NOW HIRING)

Lead Bank

Commercial Loan Officer III

Kansas City, MO · On-site

First, unparalleled technical expertise from a distinguished team of developers with an extensive ... The ideal candidate brings extensive experience in business development, credit and market risk ...

next page

Showing results 1-20

People also search for

All JobsCredit Risk Developer JobsCredit Risk Developer Jobs in Missouri

Credit Risk Developer information

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

AspectCredit Risk DeveloperCredit Analyst
Required CredentialsBachelor's in Finance, Economics, or related field; often some programming knowledgeBachelor's in Finance, Economics, or related field; strong analytical skills
Work EnvironmentDevelops risk models, works with data and software toolsAnalyzes credit data, assesses borrower risk, prepares reports
Employer & Industry UsageFinancial institutions, banks, credit agenciesBanks, lending institutions, credit bureaus

While both roles focus on credit, the Credit Risk Developer primarily builds and maintains risk models using programming and data analysis, whereas the Credit Analyst evaluates individual creditworthiness and prepares risk assessments. Both roles are essential in credit decision processes but differ in technical focus and daily tasks.

What are Credit Risk Developers?

Credit Risk Developers are specialized software developers who design, build, and maintain systems that assess and manage financial risk for lending institutions or investment firms. They create algorithms and tools that analyze credit data, model potential losses, and ensure compliance with regulatory requirements. Their work supports decision-making processes related to lending, underwriting, and portfolio management. Typically, they collaborate closely with risk analysts, data scientists, and financial professionals to develop solutions that improve risk assessment accuracy and efficiency.

How does a Credit Risk Developer typically collaborate with risk analysts and business stakeholders?

A Credit Risk Developer often works closely with risk analysts to understand credit risk models and translate their requirements into robust software solutions. Regular meetings with business stakeholders are common to gather feedback, ensure alignment with regulatory standards, and adapt to changing business needs. This role requires strong communication skills to bridge the gap between technical and non-technical teams, ensuring that risk assessment tools are both accurate and user-friendly.

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

To thrive as a Credit Risk Developer, you need strong programming skills (such as Python, Java, or C++), a solid background in mathematics or finance, and experience with credit risk modeling. Familiarity with risk management systems, statistical analysis tools, and relevant certifications (like FRM or CFA) is often required. Exceptional problem-solving abilities, collaboration, and clear communication set outstanding candidates apart. These skills ensure accurate development and maintenance of credit risk models, enabling effective risk mitigation and regulatory compliance in financial institutions.
What are popular job titles related to Credit Risk Developer jobs in Missouri? For Credit Risk Developer jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Credit Risk Developer jobs in Missouri look for? The top searched job categories for Credit Risk Developer jobs in Missouri are:
What cities in Missouri are hiring for Credit Risk Developer jobs? Cities in Missouri with the most Credit Risk Developer job openings:
Credit Risk Developer jobs near you

Senior Credit Risk/Decision Scientist

TBO Bank

Kansas City, MO

Full-time

Posted 22 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.

Apply