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Risk Modeling Jobs in New York (NOW HIRING)

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 ...

KKR

VP, Credit Risk Modeling

Manhattan, NY · On-site

$160K - $175K/yr

VP, Credit Risk Modeling New York, New York, United States KKR is a leading global investment firm that offers alternative asset management as well as capital markets and insurance solutions. KKR ...

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 ...

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How much do risk modeling jobs pay per hour?

As of Sep 3, 2026, the average hourly pay for risk modeling in New York is $33.19, according to ZipRecruiter salary data. Most workers in this role earn between $21.30 and $42.36 per hour, depending on experience, location, and employer.

What is risk modeling?

Risk modeling is the process of using statistical and mathematical techniques to predict potential risks and their impact on an organization or financial system. Professionals in this field develop models to assess the likelihood and severity of various risks, such as credit, market, operational, or environmental risks. These models help organizations make informed decisions, comply with regulations, and minimize potential losses by preparing for uncertain events.

What are the key skills and qualifications needed to thrive as a risk modeler, and why are they important?

To thrive as a Risk Modeler, you need strong quantitative analysis skills, a background in statistics or mathematics, and typically a relevant degree such as finance, economics, or engineering. Familiarity with statistical software (like SAS, R, or Python), risk management frameworks, and regulatory requirements is essential, and certifications such as FRM or CFA are often valued. Attention to detail, problem-solving abilities, and effective communication help translate complex data into actionable insights for various stakeholders. These skills ensure accurate risk assessment, regulatory compliance, and informed decision-making in high-stakes environments.

What are some common challenges faced by professionals in risk modeling roles, and how are they typically addressed?

Risk modeling professionals often encounter challenges such as managing incomplete or inconsistent data, keeping up with rapidly evolving regulatory requirements, and ensuring their models remain accurate as market conditions change. To address these, teams frequently collaborate with data engineers, compliance specialists, and business stakeholders to validate data sources, implement robust model governance processes, and regularly update models. Continuous learning and cross-functional communication are key to staying effective in this dynamic environment.

What is the difference between Risk Modeling vs Risk Analyst?

AspectRisk Modeling
AspectRisk Modeling

Risk Modeling involves developing quantitative models to predict and assess potential risks using statistical and mathematical techniques. Risk Analysts interpret these models, analyze data, and provide insights to support decision-making. While Risk Modeling focuses on creating models, Risk Analysts apply these models to real-world scenarios. Both roles often require similar credentials like certifications in risk management and work in similar environments such as finance, insurance, or banking. Understanding the distinction helps organizations allocate resources effectively and professionals target their skill development.

Do risk analysts make good money?

Risk analysts typically earn competitive salaries that vary by industry, experience, and location. Entry-level positions may start lower, but with experience and advanced skills such as data analysis and risk assessment tools, salaries can increase significantly, often reaching six figures for senior roles.

What does a risk modeling do?

A risk modeler analyzes data to identify and quantify potential risks that could impact an organization, often using statistical and mathematical techniques. They develop models to predict the likelihood and impact of various risk factors, supporting decision-making and risk management strategies. Proficiency in data analysis tools and understanding of industry-specific risks are essential for this role.

What are the most commonly searched types of Risk Modeling jobs in New York?

The most popular types of Risk Modeling jobs in New York are:

What are popular job titles related to Risk Modeling jobs in New York?

For Risk Modeling jobs in New York, the most frequently searched job titles are:

What job categories do people searching Risk Modeling jobs in New York look for?

The top searched job categories for Risk Modeling jobs in New York are:

Risk Modeling jobs near you
Infographic showing various Risk Modeling job openings in New York as of August 2026, with employment types broken down into 1% As Needed, 91% Full Time, 6% Part Time, and 2% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $69,033 per year, or $33.2 per hour.

VP, Credit Risk Modeling

Careers at KKR

New York, NY • On-site

$160K - $175K/yr

Full-time

Re-posted 5 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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