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KKR

Runs private equity, credit and infrastructure funds

Actuarial Associate - Model Development and Production

Actuarial & Risk ModellingPosted on Nov 10
Full-time

About the Job

Requirements

  • A bachelor's degree in Actuarial Science, Mathematics, Statistics, Finance, Computer Science, or a related field is required.
  • A minimum ASA or equivalent designation is required.
  • At least five years of actuarial experience in the life insurance and retirement industry is required.
  • Direct work experience with or knowledge of life and annuity products and U.S. Statutory and GAAP valuation is required.
  • Experience with MG-ALFA, Integrate, Prophet, RAFM, Pathwise, or other actuarial modeling and valuation software is required.
  • Strong hands-on Python programming skills are required, including the ability to read, develop, test, and troubleshoot production code.
  • Working knowledge of PySpark and experience with ETL/data-transformation processes, large datasets, data validation, and reconciliations are required.
  • Experience with Git/source control and basic software-development change-management practices, including branches, commits, pull requests, peer review, and controlled testing, is required.
  • Strong communication, technical, and analytical skills are required to work effectively across Model Production, Model Development, Valuation, Data, and Technology teams.
  • The candidate must take ownership and be personally accountable for execution of goals and objectives.
  • The candidate must be able to participate in generating new ideas and process improvements.
  • The candidate must work effectively with others.
  • The candidate must be comfortable using AI-powered tools to improve productivity and quality of work.
  • The candidate must critically evaluate AI-generated outputs for accuracy and relevance.

Responsibilities

  • Lead and perform accurate monthly and quarterly production runs using Integrate and MG-ALFA models to calculate U.S. Statutory, Tax, U.S. GAAP reserves, and other related actuarial balances.
  • Prepare and validate model input files, including asset, liability, and scenario inputs.
  • Review and analyze model results and investigate variances.
  • Maintain evidence for SOX controls associated with production model runs.
  • Conduct annual impact testing for potential assumption changes.
  • Run models to test model updates implemented by the Model Development team.
  • Run models to provide the Valuation team with reserve impacts from model changes and support review and approval of those changes.
  • Support analysis, including sensitivities, for statutory and GAAP balances and earnings impacts.
  • Support audit and regulatory requests.
  • Develop, maintain, and troubleshoot Python and PySpark ETL processes that transform source data into production-ready actuarial model inputs and support model-output and post-processing workflows.
  • Maintain a clear source-to-model understanding for assigned production processes, including source data, mappings, reference data, transformation logic, model inputs, and key downstream dependencies.
  • Implement routine transformation, mapping, and data-processing changes using established development and change-management standards; document business logic and maintain traceable change history.
  • Build and enhance automated data-quality checks, reconciliations, exception handling, and production controls to improve completeness, accuracy, and transparency of model inputs and outputs.
  • Use Git-based source control, branches, pull requests, peer review, and documented testing to manage Python/PySpark production changes in a controlled manner.
  • Perform unit, regression, integration, and end-to-end testing of ETL and automation changes, including reconciliation to legacy or prior-period results where appropriate.
  • Support migration of legacy IDM, Excel/VBA, or other manual production processes to Python/PySpark and automated workflows, focusing on sustainable, reusable production solutions.
  • Troubleshoot production issues across source data, transformations, model inputs, model execution, and outputs; partner with Data and Technology teams when issues involve enterprise data pipelines, infrastructure, or platform services.
  • Support workflow orchestration, monitoring, and restart processes for automated actuarial production, including Dagster or comparable orchestration tooling as applicable.
  • Work closely with Model Development, Valuation, Data, Transformation, and technology teams.

Desired Qualifications

  • Familiarity with workflow orchestration and cloud-based data-processing environments such as Dagster, AWS/EMR, or comparable technologies is preferred.
  • Curiosity about and openness to adopting emerging AI technologies in day-to-day workflows.

About the Company

KKR

Runs private equity, credit and infrastructure funds

KKR is a global investment firm that raises money from pension funds, insurers, sovereign wealth funds and wealthy individuals and invests it in private equity, credit, infrastructure and real estate. It was an early pioneer of the debt-funded buyout, and its 1989 takeover of RJR Nabisco ranks among the largest buyouts ever. Through its Global Atlantic subsidiary, KKR also sells retirement annuities and life insurance and invests the premiums. It earns management fees on client money, a share of investment profits and income from its own holdings. KKR was founded in 1976 by Jerome Kohlberg, Henry Kravis and George Roberts and is based in New York City.

Company size
5,001-10,000
Company stage
IPO
Headquarters
New York City, New York
Founded
1976

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