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Hourly Credit Risk Modeling Jobs (NOW HIRING)

Careers at KKR

VP, Credit Risk Modeling

New York, NY

$160K - $175K/yr

Build and own portfolio credit risk models that quantify tail losses from default and rating migration across asset classes * Develop a credit risk framework: calibrate transition matrices, model ...

Careers at KKR

VP, Credit Risk Modeling

New York, NY · On-site

$160K - $175K/yr

Build and own portfolio credit risk models that quantify tail losses from default and rating migration across asset classes * Develop a credit risk framework: calibrate transition matrices, model ...

IDBNY

Credit Risk Analytics & Modeling

Manhattan, NY · On-site

Head of Credit Risk Analytics & Modeling Visa Sponsorship: Not available About IDB Bank For more than 70 years, IDB Bank has been committed to delivering exceptional service and building long-term ...

PSECU

Credit Risk Analyst

Harrisburg, PA · On-site

Analyzes effectiveness of credit risk models and strategies and provides insights and recommendations to leadership. Participates in projects impacting Credit Risk Management. Identifies and ...

PSECU

Credit Risk Analyst

Harrisburg, PA · On-site

Analyzes effectiveness of credit risk models and strategies and provides insights and recommendations to leadership. Participates in projects impacting Credit Risk Management. Identifies and ...

Rockland Trust

Credit Risk Oversight Officer

Norwood, MA · On-site

Review and challenge credit risk modeling practices in partnership with the Second Line Model Risk Management team, including loan loss estimation and stress testing methodologies. Risk Reporting and ...

Rockland Trust

Credit Risk Oversight Officer

Norwood, MA · On-site

Review and challenge credit risk modeling practices in partnership with the Second Line Model Risk Management team, including loan loss estimation and stress testing methodologies. Risk Reporting and ...

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Hourly Credit Risk Modeling information

What is hourly credit risk modeling?

Hourly credit risk modeling is the process of assessing and predicting the likelihood of a borrower defaulting on their financial obligations, with risk evaluated and updated on an hourly basis. This approach is often used by financial institutions and fintech companies that require real-time credit risk analysis for instant lending decisions or ongoing portfolio monitoring. By utilizing real-time data and advanced analytics, hourly credit risk modeling enables lenders to respond quickly to changes in a borrower's financial behavior or external market conditions. This leads to more accurate risk assessments and helps institutions manage their exposure more effectively.

What is the difference between Hourly Credit Risk Modeling vs Credit Analyst?

AspectHourly Credit Risk ModelingCredit Analyst
Primary FocusDeveloping and implementing credit risk models to assess borrower riskAnalyzing credit data to evaluate creditworthiness of individuals or companies
Required SkillsStatistical analysis, modeling, programming, financial analysisFinancial analysis, credit report review, communication skills
Work EnvironmentFinancial institutions, consulting firms, often project-basedBanks, lending institutions, credit departments
CertificationsOften requires CFA, FRM, or similar certificationsTypically requires finance or accounting degrees; certifications like CFA are common

Hourly Credit Risk Modeling involves creating quantitative models to predict credit risk, often requiring advanced statistical and programming skills. Credit Analysts focus on evaluating individual credit data to make lending decisions. While both roles require financial knowledge and may share certifications, their core responsibilities differ: one is model development, the other is credit evaluation.

What are the key skills and qualifications needed to thrive as an Hourly Credit Risk Modeler, and why are they important?

To thrive as an Hourly Credit Risk Modeler, you need strong quantitative skills, a background in finance, economics, mathematics, or statistics, and experience with credit risk principles. Familiarity with statistical software such as SAS, R, or Python, as well as knowledge of risk modeling frameworks and regulatory requirements, is typically required. Analytical thinking, attention to detail, and effective communication are crucial soft skills for interpreting data and presenting findings to stakeholders. These skills are essential for accurately assessing credit risk, supporting sound decision-making, and ensuring regulatory compliance in financial institutions.

How does an Hourly Credit Risk Modeling professional typically collaborate with other departments within a financial institution?

Hourly Credit Risk Modeling professionals often work closely with teams such as underwriting, data analytics, and IT to ensure credit risk models are accurate and actionable. They may participate in cross-functional meetings to discuss model performance, share insights from data analysis, and implement feedback from business stakeholders. Collaboration is key, as their models directly influence lending decisions, risk management strategies, and regulatory compliance. Regular communication with colleagues helps ensure that risk models stay aligned with evolving business needs and regulatory requirements.
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Hourly Credit Risk Modeling jobs near you
Infographic showing various Hourly Credit Risk Modeling job openings in the United States as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

VP, Credit Risk Modeling

Careers at KKR

New York, NY

$160K - $175K/yr

Other

Re-posted 3 days ago

Job description

The Opportunity

Global Atlantic, a KKR company, is one of the largest insurance and reinsurance platforms in Bermuda, managing over $110 billion across multiple entities. As the portfolio grows in scale and complexity - spanning structured credit, mortgage loans, corporate bonds, and alternative assets - we are investing in a dedicated credit modeling capability to help the firm understand and quantify tail credit risk across the full investment book. This VP role will lead the development of models that measure portfolio-level default and downgrade exposure, inform capital allocation, and strengthen our risk framework.

Responsibilities:

  • Build and own portfolio credit risk models that quantify tail losses from default and rating migration across asset classes
  • Develop a credit risk framework: calibrate transition matrices, model correlated credit migration, and produce full loss distributions to measure tail risk at the portfolio level
  • Calibrate asset-class-specific inputs - transition probabilities, loss given default, recovery rates, and credit spreads
  • Translate model outputs into actionable capital metrics: compute expected loss, cost of downgrade, and tail risk measures by rating and tenor to support portfolio construction, and limit-setting decisions
  • Build production-quality Python pipelines for model execution, data processing, and automated reporting; deliver clear visualizations and summaries for senior leadership and the Board
  • Partner with investment teams, and finance to embed credit risk analytics into portfolio monitoring, stress testing, and strategic asset allocation

Qualifications Required:

  • 8-12 years in credit risk modeling, quantitative finance, or insurance capital modeling.
  • Deep expertise in portfolio credit risk frameworks - transition matrices, Monte Carlo simulation, correlated default modeling, and tail risk measurement.
  • Production-quality Python skills.
  • Experience calibrating and validating credit models.
  • Strong written communication for technical and executive audiences.
  • Comprehensive user of AI tools.

Preferred:

  • Insurance regulatory capital experience (Bermuda, Solvency II, or NAIC RBC).
  • Structured credit modeling (CLO engines, CMBS/RMBS loss models).
This is the expected annual base salary range for this New York-based position. Actual salaries may vary based on factors, such as skill, experience, and qualification for the role. Employees may be eligible for a discretionary bonus, based on factors such as individual and team performance.  Base Salary Range   -  $160,000 to $175,000
 
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