The most valuable finance professionals don't predict the future. They allocate capital, assess risk, and make decisions when outcomes remain uncertain.
Mercor connects finance professionals with frontier AI labs building the next generation of systems for analysis, risk assessment, and forecasting. Get matched to remote, paid projects starting at $50/hr.
Collaborate on projects that push the boundaries of what AI can do in finance, from valuation and modeling to investing, forecasting, and financial reporting.
Contribute from anywhere and choose projects that fit your schedule. Work independently without fixed hours or long-term commitments.
Rates range from $50–$180/hour based on expertise and project complexity.
Ensure models understand the nuances behind financial decisions; from evaluating an LBO to recognizing when a narrative is not supported by underlying business fundamentals.
Each project is different, but finance experts typically contribute in four ways:
Review AI-generated financial models, investment recommendations, spreadsheets, and presentations across realistic business and market scenarios. Determine whether conclusions reflect sound financial reasoning.
Develop high-quality investment theses, financial forecasts, and evaluation frameworks that help establish the benchmark for financial reasoning.
Design realistic scenarios that expose weaknesses in analysis and assess how models perform when assumptions break down or market conditions change.
Apply expert oversight to identify flawed assumptions and analytical errors. Ensure outputs are rigorous, internally consistent, and aligned with real-world financial standards.
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Evaluate how models analyze investment opportunities, from initial screening through final investment recommendation, and whether outputs identify material risks.
Assess investment decisions in dynamic market environments. Projects may involve public equities, fixed income, credit, portfolio construction, risk management, and evaluating how changing economic conditions influence investment outcomes.
Examine how businesses grow, generate cash flow, and create value over time. Projects may involve forecasting operating performance, building financial models, and stress-testing assumptions across different business scenarios.
Examine whether outputs identify material issues and have the capacity to distinguish between superficial analysis or insights across financial statements and disclosures.
Work on problems involving acquisitions, financing decisions, and capital deployment that require the ability to engage in the tradeoffs involved in creating long-term shareholder value.
Most finance projects require significant professional experience in investing, capital markets, corporate finance, accounting, or related fields. Strong candidates can independently evaluate complex financial scenarios and explain their reasoning clearly.
Evaluate
Valuation analyses, investment recommendations, and financial forecasts
Financial models, market analyses, and business assessments
Financial statements, accounting treatments, and risk evaluations
Create
Gold-standard financial analyses and benchmark responses
Evaluation rubrics and reviewer calibration frameworks
Realistic investment cases, business scenarios, and financial datasets
Test
How models handle uncertainty, missing information, and competing assumptions
Reasoning quality in forecasting, valuation, and capital allocation decisions
Whether models identify key risks and validate conclusions before making recommendations
Review
Analytical rigor, financial accuracy, and professional quality
Internal consistency, assumption quality, and reasoning strength
Communication clarity and decision-making frameworks
Experience with financial modeling, valuation, transaction execution, investment analysis, forecasting, financial reporting, capital allocation, portfolio management, or risk assessment is commonly relevant across projects.
No. The work is closer to professional financial analysis, investment evaluation, and expert review than traditional prompt writing or data labeling.
Strong candidates typically have:
Professional experience in finance, investing, accounting, or capital markets
The ability to independently establish ground truth and evaluate analytical quality
Strong judgment around risk, uncertainty, and decision-making
Clear written communication and the ability to explain reasoning
The ability to apply consistent evaluation standards across complex financial scenarios
Compensation varies by project, specialization, and experience level.
Recent opportunities have included:
Qualified specialists and highly experienced finance professionals may receive access to additional premium opportunities.