Sompo International

Sompo International

Senior Quality Control Analyst

Remote, Kentucky, USA · Senior · Full-time

Sponsorship not specifiedDetected 15 days ago
ResearchCommunicationCollaborationMicrosoft OfficeUnderwriting

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odds of building a lasting career here

16Unrated
Cap-exempt (no lottery)0
Sponsors this role0
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

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About the role

  • Are you looking for your next opportunity?
  • AgriSompo has a unique opportunity for a Crop Insurance Senior Quality Control Analyst for our Quality Control team.
  • Your responsibilities will primarily focus on conducting production history audits, policy reviews, and claim assessments.

Requirements

  • Assist in the continuous monitoring and the reporting processes as required by the SRA.

Nice to have

  • Preferred CAPP Certification, but not required
  • Proficiency in computer skills, including working knowledge of Microsoft Office Suite including Outlook plus PDF program
  • Bachelor's degree in agriculture or a related field is preferred, but not required

Skills

  • AgriSompo North America has major offices in Lenexa, Kansas and Des Moines, Iowa as well as regional offices around the country.

Compensation

  • This is why we offer competitive, high-quality compensation and benefit programs to eligible employees.

Company info

  • AgriSompo North America is a part of AgriSompo, Sompo International's global agriculture platform.
  • We strive to foster a workplace where everyone feels respected, included, and empowered to excel.
  • Life at Sompo page Our values come to life in how we hire and grow talent.
  • Our values come to life in how we hire and grow talent.
  • Employment decisions are based on qualifications, merit, and organizational need, and we strive to ensure equitable access to opportunities so everyone can do their best work.

Equal opportunity

  • If you need an accommodation for any part of the

This listing is sourced directly from Sompo International's careers page and normalized into a canonical job model.