Remote M&A Finance Researcher - Equity Options

micro1; United States; Remote; USD 200,000 - 250,000; Full time

Benefits offered by this job

Equity compensation

Health-insurance premium reimbursement

401(K) plan with company match

Paid time off

Job summary

micro1 is seeking a Domain Researcher, Finance (M&A) for a remote full-time role. You will design evaluation frameworks, benchmarks, and scoring methodologies for AI agents operating in corporate development and M&A workflows.

You will assess AI-generated financial analyses, valuation models, acquisition assessments, and investment recommendations, translating real-world M&A experience into structured datasets and measurable criteria.

Qualifications

• Strong background in corporate development, M&A, banking or PE.
• Experience across M&A lifecycle: screening, valuation, due diligence, deal analysis.
• Ability to translate financial workflows into research questions and evaluation criteria.

Responsibilities

• Design evaluation frameworks, benchmarks, and scoring methodologies for AI in M&A workflows.
• Create test cases covering acquisition screening, valuation, due diligence, and deal structuring.
• Evaluate AI-generated financial analyses, valuation models, and investment recommendations.
• Translate M&A experience into structured datasets, research scenarios, and criteria.
• Collaborate with AI researchers, engineers, and product teams to identify model limitations and improve financial reasoning.

Skills

M&A experience

Corporate development

Investment banking

Private equity

Strategic investments

Education

Bachelor's degree in Finance/Economics/Business

Tools

Excel

Python

SQL

Job description

micro1 is seeking a Domain Researcher, Finance (M&A) for a remote full-time role. You will design evaluation frameworks, benchmarks, and scoring methodologies for AI agents operating in corporate development and M&A workflows.

You will assess AI-generated financial analyses, valuation models, acquisition assessments, and investment recommendations, translating real-world M&A experience into structured datasets and measurable criteria.