FP&A / Corporate Finance Evaluator
New
J
JobgetherFinance / AI
United StatesContractSenior
Salary80 - 120 USD per hour
Apply NowOpens the employer's application page
Job Details
- Languages
- English
- Experience
- 5+ years
- Required Skills
- Microsoft ExcelPowerPointBudgeting
Requirements
- 5+ years of relevant professional experience in FP&A, corporate finance, financial planning and analysis, or a closely related discipline.
- Strong knowledge of financial planning, budgeting, forecasting, management reporting, financial modeling, and business performance analysis.
- Native or professional fluency in English, with strong written and verbal communication skills.
- Highly proficient in Microsoft Office and Google Workspace, particularly Excel, PowerPoint, and Google Slides.
- Strong analytical, critical-thinking, and problem-solving capabilities, with exceptional attention to detail.
- Ability to critically evaluate financial analyses and distinguish sound reasoning from inaccurate or unsupported conclusions.
- Ability to communicate complex financial concepts and provide concise, structured feedback.
- Comfortable working independently in a fully remote environment and collaborating asynchronously with a research team.
- Preferred: Master’s degree or higher from a reputable institution.
Responsibilities
- Evaluate AI-generated financial documents, spreadsheets, and slide decks against established FP&A and corporate finance quality standards.
- Assess outputs for financial accuracy, analytical rigor, logical consistency, completeness, and relevance.
- Identify factual errors, flawed calculations, analytical gaps, inconsistencies, and weaknesses in financial reasoning.
- Review the quality and effectiveness of financial presentations, including structure, clarity, formatting, and visual communication.
- Apply subject-matter expertise to determine whether AI-generated work reflects appropriate corporate finance and FP&A practices.
- Provide clear, structured, and actionable written feedback to explain deficiencies and opportunities for improvement.
- Consistently apply domain-specific evaluation criteria when grading AI-generated work products.
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