VP, Credit Risk Modeling

United States·New Yorkmid

OtherCredit Risk

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Quick Summary

Key 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,

Requirements Summary

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,

Technical Tools

OtherCredit Risk

KKR is a leading global investment firm that offers alternative asset management as well as capital markets and insurance solutions. KKR aims to generate attractive investment returns by following a patient and disciplined investment approach, employing world-class people, and supporting growth in its portfolio companies and communities. KKR sponsors investment funds that invest in private equity, credit and real assets and has strategic partners that manage hedge funds. KKR’s insurance subsidiaries offer retirement, life and reinsurance products under the management of Global Atlantic Financial Group. References to KKR’s investments may include the activities of its sponsored funds and insurance subsidiaries.

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

~1 min read

→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

Requirements

~1 min read

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.

Nice to Have

~2 min read

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

#LI-Onsite

KKR is an equal opportunity employer. Individuals seeking employment are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, sexual orientation, or any other category protected by applicable law.

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