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.
Responsibilities
- 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
Requirements
- 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
Nice to Have
- 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
Why Join
- 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