Senior Auto Claims Adjuster – Freelance AI Trainer

<p><em>Please submit your CV in English and indicate your level of English proficiency. </em></p> <p>Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. <strong>Participation is project-based, not permanent employment.</strong></p> <p><strong>What this opportunity involves</strong></p> <p>While each project involves unique tasks, contributors may:</p> <ul> <li>Evaluate AI-generated auto insurance claims decisions for accuracy, coverage correctness, and regulatory compliance;</li> <li>Design realistic FNOL (First Notice of Loss) scenarios with deliberate contradictions, decoy files, and outdated documents to test agent robustness;</li> <li>Create test cases for coverage-scope decisions (collision vs. comprehensive) where the correct answer requires domain knowledge, not keyword matching;</li> <li>Write and grade fraud-flagging scenarios using structured reason codes (late reporting, recently purchased policy, inconsistent damage) for SIU referral;</li> <li>Build subrogation test cases applying state-specific negligence rules (comparative vs. contributory) and assess likelihood of recovery;</li> <li>Develop supervisor-escalation scenarios that test whether the agent correctly recognizes authority-limit thresholds ($25,000) and stops short of auto-approving;</li> <li>Draft and evaluate reservation-of-rights letter scenarios, verifying language stays within the bad-faith line;</li> <li>Validate coverage-limits math when multiple endorsements (OEM, rideshare, extended rental) stack on a single claim;</li> <li>Document test cases clearly with correct answers, policy citations, and payout calculations.</li> </ul> <p><strong>What we look for</strong></p> <p>This opportunity is a good fit for mortgage underwriters and loan origination professionals open to part-time, non-permanent projects. Ideally, contributors will have:</p> <ul> <li>Degree in Finance, Business, Insurance, or related field — or equivalent professional experience; no specific degree is required if AIC, CPCU, or comparable credentials are present, or if the candidate has 4+ years of hands-on claims adjusting experience;</li> <li>3+ years of hands-on auto claims adjusting, examining, or supervisory experience at a U.S. carrier, independent adjusting firm, or SIU team;</li> <li>Ability to make coverage decisions (collision vs. comprehensive, endorsement stacking, exclusion vs. coverage grant) without looking them up;</li> <li>Familiarity with U.S. state-specific rules — comparative vs. contributory negligence states, state adjuster licensing requirements;</li> <li>Experience reading full auto policy documents with citation discipline (able to reference a specific section, e.g. "Section IV.B.2");</li> <li>Comfort computing payout math involving deductibles, sub-limits, and layered endorsements in Excel or equivalent;</li> <li>Awareness of the bad-faith line and adjuster authority-limit culture;</li> <li>Associate in Claims (AIC), CPCU, CIFI, or SCLA credential is a strong positive signal — but not required if experience is solid;</li> <li>Strong written English (C1+).</li> </ul> <p><strong>How it works </strong></p> <p>Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid</p> <p><strong>Project time expectations </strong></p> <p>For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. </p> <p><strong>Compensation </strong></p> <p>On this project, contributors can earn up to <strong>$60 per hour equivalent</strong>, depending on their level and pace of contribution. </p> <p>Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.</p>