About the Opportunity
A leading AI research organization is starting a focused Finance Sprint within Project Mercury in the next 24 hours. We are seeking experienced finance professionals to evaluate whether individual workflows and tasks accurately reflect real professional practice in their specialist domain.
Offers are first-come, first-served. This will be a high-engagement project over the next week, so please apply only if you can stay actively involved throughout the sprint. Work may involve completing multi-hour tasks in one sitting, typically around 2–4 hours, and requires keeping Slack notifications on and responding to project updates, questions, and feedback within the day.
This is a workflow-realism evaluation engagement. You will use your professional judgment to assess whether each task, its provided context, expected workflow, and constraints would make sense in real practice. The exact task content is confidential and may vary during the sprint.
What You'll Do
Who We're Looking For
5–9 years of relevant experience for the practitioner track, or 9–15 years for the senior reviewer track
Professional experience in fundamental equity research, asset management, hedge funds, or a closely related investing role
Strong financial-statement analysis, forecasting, valuation, and investment-judgment skills
Experience covering TMT or semiconductors, or conducting event-driven and SEC-filings-intensive research, is a strong plus
Excellent written communication and the ability to explain not only whether something is correct, but why
High attention to detail, sound professional judgment, and comfort evaluating work against explicit standards
Experience reviewing analysts, approving work, designing controls, or setting quality standards is especially valuable for the senior track
Why This Work Matters
High-quality AI evaluation depends on tasks that reflect genuine professional practice, not just plausible-looking work. Your expertise will help ensure this sprint measures meaningful finance capability with rigor and consistency.