Expert Equities Research Reviewer

Mercor is hiring Expert Equities Research Reviewers on behalf of a team building an autonomous, AI-powered deep research system for public equities analysis. This system generates multi-source investment research reports, including financial modeling, valuation analysis, competitive positioning, price targets, and structured investment theses. In this role, you will evaluate AI-generated reports for accuracy, analytical depth, and practical investment utility — helping calibrate and improve a system designed to operate at institutional research standards. This is a high-judgment role suited for experienced investment professionals.

Review AI-generated equity research reports for factual accuracy, analytical rigor, and logical coherence

Expert Equities Research Reviewers

Responsibilities

factual accuracy, analytical rigor, and logical coherence

current market realities

Requirements

public equities research, portfolio management, or related buy-side/sell-side roles

fundamental analysis

Nice to Have

Why Join

Mercor is hiring Expert Equities Research Reviewers on behalf of a team building an autonomous, AI-powered deep research system for public equities analysis. This system generates multi-source investment research reports, including financial modeling, valuation analysis, competitive positioning, price targets, and structured investment theses. In this role, you will evaluate AI-generated reports for accuracy, analytical depth, and practical investment utility — helping calibrate and improve a system designed to operate at institutional research standards. This is a high-judgment role suited for experienced investment professionals. Review AI-generated equity research reports for factual accuracy, analytical rigor, and logical coherence Evaluate investment theses, price targets, and buy/hold/sell recommendations, identifying unsupported assumptions or gaps in reasoning Verify financial metrics and modelling logic across: Revenue growth and margin structure Rule of 40 calculations TAM estimates Valuation multiples and DCF assumptions Assess whether conclusions reflect current market realities and align with publicly available information Provide structured written feedback across key quality dimensions, including: Source reliability Claim confidence calibration Internal consistency Completeness of coverage Flag stale data, misinterpreted metrics, flawed valuation logic, or missing contextual factors that could mislead an investment decision-maker Evaluate multi-company comparative analyses and sector-level assessments for methodological soundness and practical relevance Professional experience in public equities research, portfolio management, or related buy-side/sell-side roles (hedge fund, asset management, equity research, or investment banking) Strong command of fundamental analysis, including: Financial statement interpretation DCF modelling and valuation methodologies Comparable company analysis Earnings-driven forecasting Ability to critically assess an investment thesis and deliver clear, specific, and actionable written feedback Comfort reviewing structured research documents (Markdown or PDF format) Strong written communication skills — feedback must be precise, analytical, and constructive CFA designation or active progress toward it Experience building or evaluating quantitative research tools, screening systems, or systematic strategies Familiarity with AI/LLM capabilities and limitations in financial research contexts Coverage experience across multiple sectors beyond technology Shape the quality standard for a frontier AI system operating at institutional-grade research levels Collaborate with engineers and AI researchers building multi-agent financial analysis systems Directly influence how AI-generated equity research is validated, calibrated, and improved Join a global network of senior finance professionals contributing to the next generation of AI-assisted investment research We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.

• Review AI-generated equity research reports for factual accuracy, analytical rigor, and logical coherence
• Evaluate investment theses, price targets, and buy/hold/sell recommendations, identifying unsupported assumptions or gaps in reasoning
• Verify financial metrics and modelling logic across:

Revenue growth and margin structure

Rule of 40 calculations

TAM estimates

Valuation multiples and DCF assumptions

• Revenue growth and margin structure
• Rule of 40 calculations
• TAM estimates
• Valuation multiples and DCF assumptions
• Assess whether conclusions reflect current market realities and align with publicly available information
• Provide structured written feedback across key quality dimensions, including:

Source reliability

Claim confidence calibration

Internal consistency

Completeness of coverage

• Source reliability
• Claim confidence calibration
• Internal consistency
• Completeness of coverage
• Flag stale data, misinterpreted metrics, flawed valuation logic, or missing contextual factors that could mislead an investment decision-maker
• Evaluate multi-company comparative analyses and sector-level assessments for methodological soundness and practical relevance
• Revenue growth and margin structure
• Rule of 40 calculations
• TAM estimates
• Valuation multiples and DCF assumptions
• Source reliability
• Claim confidence calibration
• Internal consistency
• Completeness of coverage
• Professional experience in public equities research, portfolio management, or related buy-side/sell-side roles (hedge fund, asset management, equity research, or investment banking)
• Strong command of fundamental analysis, including:

Financial statement interpretation

DCF modelling and valuation methodologies

Comparable company analysis

Earnings-driven forecasting

• Financial statement interpretation
• DCF modelling and valuation methodologies
• Comparable company analysis
• Earnings-driven forecasting
• Ability to critically assess an investment thesis and deliver clear, specific, and actionable written feedback
• Comfort reviewing structured research documents (Markdown or PDF format)
• Strong written communication skills — feedback must be precise, analytical, and constructive
• Financial statement interpretation
• DCF modelling and valuation methodologies
• Comparable company analysis
• Earnings-driven forecasting
• CFA designation or active progress toward it
• Experience building or evaluating quantitative research tools, screening systems, or systematic strategies
• Familiarity with AI/LLM capabilities and limitations in financial research contexts
• Coverage experience across multiple sectors beyond technology
• Shape the quality standard for a frontier AI system operating at institutional-grade research levels
• Collaborate with engineers and AI researchers building multi-agent financial analysis systems
• Directly influence how AI-generated equity research is validated, calibrated, and improved
• Join a global network of senior finance professionals contributing to the next generation of AI-assisted investment research