Finance & Accounting Specialist – Rubric Design

In this hourly, remote contractor role, you will work as a Finance & Accounting Subject Matter Expert (SME) to create realistic professional tasks, evaluate AI-generated financial work, and design detailed rubrics defining what a high-quality professional response should contain. You will develop challenging questions and work products involving areas such as financial analysis, accounting, corporate finance, investment analysis, valuation, financial modeling, reporting, audit, risk, or related disciplines. You will assess whether AI outputs use appropriate assumptions, methodologies, calculations, professional judgment, and supporting reasoning. A major focus of this role is rubric design and evaluation writing. You will translate professional finance and accounting judgment into structured criteria covering accuracy, methodology, completeness, materiality, assumptions, calculations, risk considerations, and quality of reasoning. You may also critique and improve rubrics developed by other experts. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your expertise directly helps improve the world’s premier AI models by making financial outputs more accurate, rigorous, and professionally useful.

Responsibilities

• Create professional finance tasks: Develop challenging financial, accounting, valuation, investment, audit, or analytical problems.
• Design scoring rubrics: Define the calculations, assumptions, reasoning, and professional considerations expected in strong responses.
• Evaluate financial outputs: Review AI-generated analyses for accuracy, methodology, logic, and completeness.
• Assess professional judgment: Determine whether assumptions and conclusions are reasonable and sufficiently supported.
• Identify material errors: Detect incorrect calculations, accounting treatment, valuation logic, financial interpretation, or risk analysis.
• Critique peer rubrics: Review criteria for ambiguity, missing components, duplication, excessive subjectivity, or technical errors.
• Develop reference content: Produce high-quality analyses, solutions, critiques, and explanations.
• Support AI training: Generate tasks, rubrics, evaluations, preferences, and reference-answer pairs suitable for RL and SFT.
• Maintain professional standards: Ensure outputs reflect appropriate finance and accounting conventions and terminology.

Requirements

• Bachelor’s degree or higher in Finance, Accounting, Economics, Business, Applied Mathematics, or a related discipline.
• Relevant professional certifications such as CPA, CFA, ACCA, ACA, CMA, FRM, or equivalent are strongly preferred where applicable.
• Strong professional proficiency in English, minimum C1.
• 3+ years of professional experience in finance, accounting, investment analysis, corporate finance, financial reporting, audit, consulting, risk, or a related field.
• Strong knowledge of professional methodologies, calculations, assumptions, and analytical standards relevant to your specialty.
• Ability to create realistic professional finance or accounting tasks that require judgment rather than simple factual recall.
• Strong ability to design detailed rubrics covering accuracy, methodology, assumptions, completeness, materiality, reasoning quality, and professional presentation.
• Ability to distinguish between calculation errors, methodological errors, unsupported assumptions, and reasonable professional differences.
• Comfortable critiquing rubrics created by other finance or accounting experts.
• High attention to detail when reviewing numerical accuracy, financial logic, terminology, assumptions, reconciliations, and conclusions.
• Experience with training, examination writing, audit review, investment committee review, financial QA, research review, or professional assessment is strongly preferred.
• Prior experience with AI evaluation, model benchmarking, annotation, RLHF, or rubric-based scoring is preferred.