Reserv
Trucking Total Loss Adjuster
Atlanta, GA (Remote)
No sponsorshipDetected 2 hours ago
ValuationLogisticsCustomer SupportCommunicationProblem SolvingOrganizational SkillsClaims Management
About the role
- We are seeking a highly organized and detail-oriented Trucking Total Loss Adjuster to join our Transportation Claims team.
- In this role, you'll specialize in managing total loss claims for heavy-duty and commercial vehicles, working directly with fleet managers, repair shops, salvage yards, independent adjusters, and valuation vendors to expedite accurate and fair settlements.
- You'll be responsible for reviewing damage appraisals and determining when units are economically impractical to repair, coordinating salvage disposition, and verifying total loss valuations based on vehicle specs, condition, mileage, and configuration.
Responsibilities
- You'll also be expected to analyze downtime and loss-of-use exposures and manage rental and replacement vehicle considerations when applicable.
- If building a leading TPA and the prospect of tackling the long-standing challenges of the claims role sounds exciting, we can't wait to meet you.
Requirements
- If you believe you are a good fit for this role, we would love to hear from you!
Benefits
- Generous family leave policy after 8 months of continuous work Work from anywhere to facilitate your work life balance Apple laptop, large second monitor, and other quality-of-life equipment you may want.
Company info
- Founded by insurtech veterans with deep experience in SaaS and digital claims, Reserv is venture-backed by Bain Capital and Altai Ventures and began operations in May 2022.
- We are focused on automating highly manual tasks to tackle long-standing problems in claims and set a new standard for TPAs, insurance technology providers, and adjusters alike.
- About the role We are seeking a highly organized and detail-oriented Trucking Total Loss Adjuster to join our Transportation Claims team.
This listing is sourced directly from Reserv's careers page and normalized into a canonical job model.