Enterprise Insurance Scenario Designer for AI Evaluations

ixolabs.ai

France

Sur place

EUR 66 000 - 78 000

Plein temps

Il y a 3 jours
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Résumé du poste

ixolabs.ai seeks senior insurance practitioners to create paid AI evaluation material reflecting the demands of Fortune 500 carriers, reinsurers, or corporate insurance functions. Expertise with Fortune 500 carriers, reinsurers or corporate insurance functions is required.

Outputs include full scenarios, supporting information, a reference response and an assessment rubric with explanations linking evidence to outcomes.

Qualifications

  • Minimum five years in underwriting, claims, actuarial work or risk management at a Fortune 500 insurer or equivalent.
  • Experience owning underwriting portfolios, claims processes or pricing models at scale.
  • Strong command of enterprise insurance tools, reserving and regulatory compliance.

Responsabilités

  • Build cases involving difficult commercial underwriting and multi-stakeholder claims decisions.
  • Cover underwriting/exposure assessment, pricing and reserves, reinsurance decisions, regulatory practice.
  • Reproduce operational constraints using Guidewire, Duck Creek, SAS, R and actuarial models.
  • Apply actuarial risk methods and NAIC requirements to explain approaches.
  • Provide underwriting guidance, claims-handling strategies and risk explanations for senior decision-makers.
  • Write scoring guides that promote defensible enterprise judgment.

Connaissances

Underwriting experience
Claims processing
Actuarial risk management
Enterprise insurance tools

Outils

Guidewire
Duck Creek
SAS
R
Actuarial models

Description du poste

ixolabs.ai seeks senior insurance practitioners to create paid AI evaluation material reflecting the demands of Fortune 500 carriers, reinsurers, or corporate insurance functions. Expertise with Fortune 500 carriers, reinsurers or corporate insurance functions is required.

Outputs include full scenarios, supporting information, a reference response and an assessment rubric with explanations linking evidence to outcomes.

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