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Credit Risk Modeling Jobs (NOW HIRING)

Citibank, N.A. seeks a Credit Risk Senior Officer I for its Irving, Texas location. Duties ... As Model Sponsor, engage with Model Developer team to develop or update internal Risk Rating Models.

Citibank, N.A. seeks a Credit Risk Senior Officer I for its Irving, Texas location. Duties ... As Model Sponsor, engage with Model Developer team to develop or update internal Risk Rating Models.

Experience with credit risk modeling and statistical analysis. Responsibilities: * Conduct comprehensive financial analysis of clients to assess credit risk and determine credit limits. * Review and ...

Experience with credit risk modeling and statistical analysis. Responsibilities: * Conduct comprehensive financial analysis of clients to assess credit risk and determine credit limits. * Review and ...

Mine, model, analyze large datasets, and utilize predictive modeling techniques with an emphasis on optimizing credit risk and marketing campaign performance using the following predictive modeling ...

Mine, model, analyze large datasets, and utilize predictive modeling techniques with an emphasis on optimizing credit risk and marketing campaign performance using the following predictive modeling ...

Mine, model, analyze large datasets, and utilize predictive modeling techniques with an emphasis on optimizing credit risk and marketing campaign performance using the following predictive modeling ...

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Credit Risk Modeling information

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$124.5K

$145.1K

$187.5K

How much do credit risk modeling jobs pay per year?

As of Jun 3, 2026, the average yearly pay for credit risk modeling in the United States is $145,100.00, according to ZipRecruiter salary data. Most workers in this role earn between $132,500.00 and $148,500.00 per year, depending on experience, location, and employer.

What is a Credit Risk Modeling job?

A Credit Risk Modeling job involves developing statistical models and analytical techniques to assess the credit risk of individuals or businesses. Professionals in this role analyze financial data, borrower behavior, and economic trends to predict the likelihood of default and assist in making informed lending decisions. They use techniques such as logistic regression, machine learning, and Monte Carlo simulations to quantify risk. Credit risk modelers work closely with risk management teams, regulators, and financial institutions to ensure compliance with industry standards. Their insights help optimize loan approvals, set credit limits, and manage overall portfolio risk.

What are the key skills and qualifications needed to thrive in the Credit Risk Modeling position, and why are they important?

To thrive in Credit Risk Modeling, you need strong analytical skills, proficiency in statistics and finance, and typically a degree in mathematics, statistics, economics, or a related field. Familiarity with programming languages like Python, R, or SAS, as well as experience using statistical modeling software and risk management platforms, are highly valued. Excellent communication, critical thinking, and collaborative abilities help translate complex data insights for stakeholders and work effectively within cross-functional teams. These skills are crucial for designing accurate risk models that inform sound lending decisions and maintain financial stability for organizations.

What are typical daily responsibilities for someone working in Credit Risk Modeling?

Professionals in Credit Risk Modeling spend their days developing and validating statistical models to assess the likelihood of credit defaults, analyzing large data sets to identify risk factors, and compiling detailed reports on their findings. They collaborate closely with data scientists, underwriters, credit analysts, and sometimes regulatory teams to ensure models meet business and compliance standards. Additionally, they often participate in meetings to discuss portfolio performance or proposed policy changes. This role involves a balance of technical analysis, documentation, and cross-functional communication, making it dynamic and integral to financial decision-making.
What cities are hiring for Credit Risk Modeling jobs? Cities with the most Credit Risk Modeling job openings:
What are the most commonly searched types of Credit Risk Modeling jobs? The most popular types of Credit Risk Modeling jobs are:
What states have the most Credit Risk Modeling jobs? States with the most job openings for Credit Risk Modeling jobs include:
Infographic showing various Credit Risk Modeling job openings in the United States as of May 2026, with employment types broken down into 2% As Needed, 75% Full Time, 21% Part Time, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $145,100 per year, or $69.8 per hour.
Credit Risk Analytics Manager-Finance

Credit Risk Analytics Manager-Finance

BankUnited

Hialeah Gardens, FL

Full-time

Posted 6 days ago


Job description

SUMMARY: Reporting to the Director of ACL, the Credit Risk Analytics Manager is part of a dynamic team of talented professionals whose task is to manage and maintain the credit risk models used to produce the allowance for credit losses (ACL) and other credit risk estimates. The Credit Risk Analytics Manager uses a combination of quantitative, modeling, communication, and technical reporting skills to manage third-party credit risk models and lead rigorous model validations, back testing, monitoring, and governance processes. ESSENTIAL DUTIES AND RESPONSIBILITIES include the following. Other duties and special projects may be assigned.
  • SME for Moody's credit risk models CMM, RiskCalc, and MPA, coordinating model releases, inputs, overlays, change logs and stewarding data quality and lineage for production use.
  • Leads end-to-end validation lifecycle with Model Risk Management, Internal Audit, and external validators: assemble validation packages, respond to findings, track remediation actions, and maintain current model inventory and governance.
  • Maintains and updates comprehensive model documentation (purpose, data lineage, key assumptions, segmentation, limitations, monitoring thresholds) to meet regulatory/audit expectations
  • Designs and executes ongoing performance monitoring and back testing, produce concise insights, and recommend remediation/challengers if warranted
  • Advance/benchmark model usage by leveraging internal and external data to improve accuracy and business utility for CECL, attribution, and risk decomposition
  • Supports the quarterly CECL production cycle in partnership with the ACL manager
  • Builds recurring and ad-hoc dashboards and reports (Tableau, Excel, PowerPoint, Word) for senior and technical audiences.
  • Partners with Data/Technology on data quality and controls, metadata/lineage, and fit-for-purpose datasets supporting validation and CECL activities.
  • Adheres to and complies with applicable, federal and state laws, regulations and guidance, including those related to anti-money laundering (i.e. Bank Secrecy Act, US PATRIOT Act, etc.).
  • Adheres to Bank policies and procedures and completes required training.
  • Identifies and reports suspicious activity.
SUPERVISORY RESPONSIBILITIES
  • Supervises function, projects or services and/or one or more employees, as applicable.
  • Carries out supervisory responsibilities in accordance with the organization's policies and applicable laws.
  • Responsibilities include interviewing, hiring, and training employees; planning, assigning, and directing work; appraising performance coaching; rewarding and disciplining employees; addressing complaints and resolving problems.
EDUCATION Bachelor's Degree in a quantitative discipline (eg Statistics, Finance, Mathematics, Engineering, Economics) required. Advanced degree in a quantitative discipline (PhD or MSc in a STEM discipline or Economics/Finance) preferred. EXPERIENCE
  • 5+ years' experience in financial services with significant exposure to credit risk analytics/modeling required
  • Deep understanding of credit risk concepts (PD, LGD,and EAD) and credit risk models (PD/LGD, Scorecards, among others) required
  • Demonstrated direct experience of model ownership/monitoring, model development, and/or model validation, including concepts such as backtesting, sensitivity testing, and benchmarking required
  • Experience with statistical and quantitative modeling techniques is required required
  • Experience with programming and statistical packages languages, particularly Python, required required
  • Strong experience building dashboards and structured reporting packages required
CERTIFICATES, LICENSES, REGISTRATIONS
  • CFA, PRM, FRM a plus.
KNOWLEDGE, SKILLS AND ABILITIES
  • Excellent communication skills with the ability to analyze and explain findings and remediations.
  • Working knowledge with model risk management regulatory guidance (SR 11-7, OCC 2011-12, FDIC FIL-22-2017)
  • Ability to work under pressure, meet deadlines, manage competing initiatives and adapt to an ever-changing work pace with a focus on accuracy and attention to detail.
  • Strong interpersonal skills to aid in working with different divisions within the company
ADDITIONAL INFORMATION
  • Candidates residing in locations within BankUnited's footprint may be given preference.
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