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Senior Analyst - ALM Model Development

KKR

Senior 🇬🇧 English
Python C++ SQL NumPy SciPy Pandas Polars CI/CD pipelines

Job description

About the role

The Global Atlantic Bermuda team is looking for a technically strong Senior Analyst to enhance and expand its proprietary ALM projection platform. This role blends actuarial expertise with hands‑on Python and SQL development to support valuation, capital calculation, and embedded value reporting across multiple insurance entities.

Key responsibilities

  • Support code development, enhancement and deployment of the ALM projection model used for quarterly Bermuda Economic Balance Sheet (EBS) valuation, BSCR capital calculation, and Embedded Value reporting.
  • Develop EBS forecasting capabilities to support FP&A, Deal Team, and new‑business modeling.
  • Build and optimise numerical solvers for asset‑liability matching and portfolio optimisation.
  • Design and maintain automated unit tests and CI/CD pipelines to ensure precision and reproducibility of actuarial and asset projection outputs across model releases.
  • Collaborate with Actuarial, Investment and Risk teams to ensure asset assumptions and ALM strategies are accurately reflected in projections.
  • Review and challenge model results to guarantee accuracy, reasonableness, and regulatory compliance.

Required profile

  • Bachelor’s degree in actuarial science, mathematics, statistics, finance or a related field.
  • ASA designation or progress toward ASA with 3–6 years of experience in life and annuity insurance (preferred).
  • Strong Python and C++ programming skills; comfortable contributing to a production codebase.
  • Experience with numerical computing libraries (NumPy, SciPy) and data‑manipulation tools (Polars, Pandas or similar).
  • Proficiency in SQL and experience with CI/CD and automated testing frameworks.

Required skills

  • Python
  • C++
  • SQL
  • NumPy
  • SciPy
  • Pandas
  • Polars
  • CI/CD pipelines
  • Automated unit testing

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Published 1 month ago

Expires 1 week from now

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