Remote AI-Driven IB Evaluation Specialist

mercor

San Francisco (CA)

Hybrid

GBP 156,000 - 229,000

Part time

14 days+
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Job summary

Mercor connects elite talent with AI research labs and operates on a remote model. We are seeking an Investment Banking Expert (Contract) to design precise grading criteria for financial deliverables and to score AI-generated and human work samples against strict criteria.

You will apply evidence-based judgment to ensure scores are reproducible and defensible, incorporating feedback from senior reviewers and iterating quickly to improve model performance while meeting deadlines.

Qualifications

  • 2+ years of investment banking experience (associate level or above).
  • Experience at leading global banks or elite advisory boutiques in M&A, coverage, or capital markets.
  • Strong fluency in three-statement and transaction modeling (DCF, LBO, comparables, merger math).
  • Excellent written communication; detail-oriented and able to withstand peer review.

Responsibilities

  • Design precise, task-specific grading criteria for real-world banking deliverables such as financial models and valuation analyses.
  • Score AI-generated and human work samples against criteria with detailed written justifications for every score.
  • Apply consistent, evidence-based judgment to ensure scores are reproducible and defensible.
  • Incorporate structured feedback from senior reviewers and iterate quickly on your work.
  • Work independently and asynchronously to meet deadlines while improving AI model performance.

Skills

Three-statement modeling
DCF modeling
LBO modeling
Comparables analysis
Merger math

Job description

Mercor connects elite talent with AI research labs and operates on a remote model. We are seeking an Investment Banking Expert (Contract) to design precise grading criteria for financial deliverables and to score AI-generated and human work samples against strict criteria.

You will apply evidence-based judgment to ensure scores are reproducible and defensible, incorporating feedback from senior reviewers and iterating quickly to improve model performance while meeting deadlines.

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