Public Sector Finance - AI trainer

Job Title: Public Sector Finance - AI Trainer

Job Type: Part-time

Location: Remote (US, Canada, UK, EU)

Job Summary

Join our customer's team as a Public Sector Finance - AI Trainer, where you will help advance AI capabilities with real-world finance data. In this dynamic role, you will seed and structure complex, messy public sector finance artifacts, collaborating closely with AI model development teams. This is a unique opportunity to shape AI training processes and make a tangible impact in the evolving field of public sector finance.

Key Responsibilities

• Source, review, and seed real-world, messy finance spreadsheets and artifacts from public sector environments.
• Analyze and interpret ambiguous financial data, providing context for AI training workflows.
• Collaborate with AI teams to improve partial models by supplying finance-adjacent insights and structure.
• Craft clear, concise written documentation for data seeding and normalization steps.
• Assist in developing processes that allow models to reconstruct, normalize, or extend unstructured data inputs.
• Engage in iterative feedback cycles with technical teams to optimize AI model learning from finance datasets.
• Champion best practices for handling broad data inputs in rapidly evolving, ambiguous project environments.

Required Skills and Qualifications

• Strong public sector finance domain knowledge or finance-adjacent experience.
• Proven ability to work with messy, incomplete, or ambiguous data sources.
• Excellent written and verbal communication skills, with a focus on clarity and detail.
• Experience collaborating remotely with technical and non-technical stakeholders.
• Comfort navigating spreadsheets, models, and “in-the-wild” financial artifacts.
• Adaptability in undefined, structure-later workflows and willingness to seed data without prompts or rubrics upfront.
• Self-motivated, organized, and responsive in a rapidly changing project environment.

Preferred Qualifications

• Experience in AI training, data annotation, or data science within a finance context.
• Background in public sector operations, accounting, or finance regulation.
• Familiarity with iterative data-driven process improvement.