About The Position

Join a leading AI research initiative focused on evaluating the realism and quality of finance workflows used to train next-generation AI systems. We are seeking experienced finance professionals with expertise in real assets, project finance, infrastructure, energy, mining, and natural resources to assess whether complex financial tasks accurately reflect real-world industry practices. This is a high-impact evaluation engagement where you'll apply your professional judgment to ensure AI training tasks mirror authentic financial workflows, decision-making processes, and analytical standards. Due to the fast-paced nature of this project, selected candidates should be available to actively participate throughout the engagement. Tasks may require dedicated work sessions of approximately 2–4 hours and timely responses to project updates and reviewer feedback.

Requirements

  • Practitioner Track: 5–10 years of relevant professional experience.
  • Senior Reviewer Track: 10–16 years of relevant professional experience.
  • Hands-on experience in one or more of the following areas: Real estate underwriting, Project finance, Infrastructure finance, Energy finance, Mining, Natural resources investing.
  • Strong expertise in: Cash-flow modeling, Financial valuation, Debt structuring, Sensitivity and scenario analysis.
  • Ability to connect legal, operational, technical, and market considerations to financial outcomes and investment decisions.
  • Excellent written communication skills with the ability to clearly explain not only whether an analysis is correct, but why.
  • Exceptional attention to detail and the ability to evaluate work against structured quality standards.

Nice To Haves

  • Experience reviewing analyst work, approving financial analyses, establishing quality controls, or developing evaluation standards.
  • Prior experience participating in AI evaluation, data annotation, workflow validation, or structured review projects is advantageous.

Responsibilities

  • Review finance workflows and task designs for professional realism, clarity, scope, and internal consistency.
  • Evaluate whether task inputs, business context, expected analyses, and decision-making processes accurately represent real-world finance practices.
  • Identify missing assumptions, ambiguous instructions, impractical constraints, unsupported requirements, and critical edge cases.
  • Flag tasks that are overly broad, unrealistic, or unlikely to effectively measure professional finance capabilities.
  • Provide concise, structured written feedback along with actionable recommendations to improve task quality and realism.
  • Collaborate with fellow finance experts when necessary to maintain consistent evaluation standards across the project.

Benefits

  • Weekly payments are processed through supported payment platforms.
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