AI Infrastructure Credit Research Analyst
New
S
SemiAnalysisAI infrastructure finance
United States/RemoteFull-TimeMiddle
Salary not disclosed
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Job Details
- Required Skills
- PythonSQLMicrosoft Excel
Requirements
- Bring deep expertise in credit markets, banking, financial intermediation, structured finance, or a related area.
- Have a bachelor's degree in financial economics or a related discipline, or equivalent professional research experience.
- Understand corporate, bank, and investment fund balance sheets.
- Independently interpret complex financial documents, including bank call reports, corporate filings, fund and BDC disclosures, ABS documentation, credit agreements, and project finance structures.
- Apply strong credit judgment to identify hidden leverage, off-balance-sheet exposure, weak collateral, refinancing risk, and structural subordination.
- Build original datasets and analytical models using strong empirical and quantitative skills.
- Validate assumptions, defend methodologies, and explain data limitations clearly.
- Produce clear, rigorous research for a professional audience and work accurately under publication deadlines.
- Demonstrate intellectual independence and willingness to publish conclusions that may differ from prevailing market views.
Responsibilities
- Analyze financing structures across the AI infrastructure buildout, including hyperscaler balance sheets, neocloud debt, GPU-backed lending, project finance, and private credit.
- Map lending relationships, financing terms, maturity profiles, structures, and the parties holding credit and asset risk.
- Build quantitative models to assess credit risk across AI infrastructure investments.
- Evaluate counterparty exposure, concentration risk, and dependencies across borrowers, lenders, investors, vendors, and infrastructure providers.
- Assess collateral value and resilience, including GPU depreciation, power purchase agreements, datacenter leases, and capacity contracts.
- Analyze interest-rate sensitivity, refinancing needs, maturity walls, covenants, and liquidity risks.
- Develop downside and stress scenarios for changes in demand, hardware values, construction, power availability, and financial conditions.
- Build proprietary datasets from financial reports, filings, securitization documents, loan agreements, and other sources.
- Produce research reports and recurring coverage, and present findings to clients and industry audiences.
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