Finance QA Lead - Remote

Key responsibilities

• Spot-check finance items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues.
• Evaluate AI-generated finance explanations, financial calculations, investment analyses, accounting interpretations, valuation workflows, risk discussions, market summaries, and problem-solving steps for accuracy, clarity, and appropriate caution.
• Communicate with trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and finance-review-specific standards.
• Respond to trainer/QA questions clearly and promptly, especially around financial reasoning, formulas, assumptions, accounting treatment, valuation logic, risk caveats, terminology, and rubric interpretation.
• Manage trainer/QA activation by DMing inactive contributors, encouraging activation, tracking follow-ups, and flagging availability issues when needed.
• Create and maintain finance project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials.
• Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and finance-specific review requirements.
• Ensure all trainers and QAs apply finance-review guidelines consistently and understand updates as projects evolve.
• Review and flag unsafe, misleading, overconfident, or non-compliant finance outputs, especially where the content could be interpreted as personalized investment, tax, accounting, lending, insurance, or financial advice.
• Identify recurring quality gaps and propose workflow improvements to build scalable QA processes for finance AI training projects.

About the role

In this hourly, remote contractor role, you will work as a Finance Quality Assurance Lead to oversee quality, consistency, and trainer performance across finance AI training projects. You will review AI-generated finance content and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure that all contributors follow the expected quality standards.