Senior Actuarial Modeling Analyst [Multiple Positions Available]

Careers at KKRNew York, NY
$131,000 - $135,000Onsite

About The Position

This position is for a Senior Actuarial Modeling Analyst at Global Atlantic Financial Company, a KKR company. The role involves defining data requirements for actuarial models, coordinating data capture with IT, maintaining data flow between the enterprise data hub (EDH) and actuarial models (INTEGRATE and MG-ALFA), and ensuring data integrity through testing and reconciliation. The analyst will also incorporate data changes into the model governance framework, set up controls, streamline data flow for efficiency, and support audit activities. Global Atlantic is a leading provider of retirement security and investment solutions, operating in the U.S., Bermuda, and Japan. As a subsidiary of KKR, it leverages KKR's investment capabilities to offer long-term financial security through various annuity, life insurance, reinsurance, and investment solutions.

Requirements

  • Bachelor’s degree (U.S. or foreign equivalent) in Actuarial Science, Mathematics, Statistics, or a related field
  • Three (3) years of experience in the life and annuity insurance industry
  • One (1) year of experience in Actuarial model input/output audit
  • One (1) year of experience with Milliman Integrate System knowledge
  • One (1) year of experience working with MG ALFA
  • One (1) year of experience with US GAAP and US statutory valuation
  • One (1) year of Programming skills such as Python or SQL

Responsibilities

  • Define the data required for actuarial and other models, and make sure the Actuarial Modeling team is receiving that data from counterparties, Third Party Administrators (TPAs), and other sources.
  • Coordinate with the IT department to ensure that the correct data is captured in our company’s enterprise data hub (EDH).
  • Update and maintain the flow of data between EDH and our actuarial models (INTEGRATE and MG-ALFA).
  • Create and maintain process to ensure that the data feeding the actuarial models are tested and reconciled.
  • Incorporate related data changes into model governance framework and help set up and execute effective controls.
  • Identify and implement ways to streamline the flow and reconciliation of actuarial data across the valuation process to maximize efficiency and control.
  • Support internal and external audit activities as well as regulatory exams and inquiries, as needed.
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