AI Infrastructure Credit Research Analyst

SemiAnalysis•,

10d•Hybrid

About The Position

SemiAnalysis is seeking an AI Infrastructure Credit Research Analyst to lead our coverage of how the global AI infrastructure buildout is financed. This role will examine who is providing capital, how financing arrangements are structured, the terms attached to that capital, and where the underlying financial risk ultimately sits. The analysis will combine SemiAnalysis’s proprietary datacenter and semiconductor supply chain data with detailed balance-sheet, credit, and financial intermediation research. The successful candidate will build the firm’s coverage of AI infrastructure credit from the ground up, producing definitive research for credit investors, limited partners, financial institutions, regulators, and other market participants.

Requirements

Deep expertise in credit markets, banking, financial intermediation, structured finance, or related areas.
Relevant background may include: Bachelors' Degree in financial economics or a related discipline, Sell-side credit or macroeconomic research, Buy-side credit research, Central bank or financial stability research, Private credit or structured finance experience, or Equivalent professional research experience.
Strong understanding of corporate, bank, and investment fund balance sheets.
Ability to independently interpret complex financial documents, including bank call reports, corporate filings, fund and BDC disclosures, asset-backed securities documentation, credit agreements, project finance structures, and special-purpose vehicle documentation.
Strong credit judgement and the ability to identify hidden leverage, off-balance-sheet exposure, weak collateral, refinancing risk, and structural subordination.
Strong empirical and quantitative skills, including the ability to build original datasets and analytical models.
Ability to validate assumptions, defend methodologies, and clearly explain the limitations of available data.
Strong written communication skills and the ability to produce clear, rigorous research for a demanding professional audience.
Ability to work accurately and efficiently under publication deadlines.
High level of intellectual independence and willingness to publish conclusions that may differ from prevailing market views.

Nice To Haves

Research or investment experience covering: Private credit, Nonbank financial institutions, Leveraged finance, Structured credit, Asset-backed securities, Project finance, Financial stability, Bank and nonbank intermediation.
Understanding of how financial intermediation has evolved since the 2008 global financial crisis.
Named authorship on published research from a: Sell-side research team, Central bank, Bank economics team, International Monetary Fund, Bank for International Settlements, or Policy or financial research institution.
Experience analyzing interest rates and the transmission of monetary policy into lending standards, credit availability, asset values, and refinancing conditions.
Familiarity with datacenters, semiconductor economics, AI infrastructure, or power markets.
Experience analyzing infrastructure financing structures or capital-intensive technology investment cycles.
Proficiency in Python, SQL, Excel, or other tools used for financial modelling and data analysis.
Experience working with large, fragmented, or difficult-to-structure financial datasets.
Strong presentation and client communication skills.

Responsibilities

Analyze the full financing stack supporting the AI infrastructure buildout, including hyperscalers balance sheets, neoclouds and AI cloud debt, GPU-backed lending, datacenter asset-backed securities, project finance, private credit funds, business development companies, special-purpose vehicles, and vendor financing arrangements.
Map financing relationships across the AI ecosystem, identifying who is lending to whom, the terms and maturity profiles of the financing, the structures through which capital is provided, and the parties ultimately holding the 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, equipment vendors, and infrastructure providers.
Model the value and resilience of collateral, including GPU depreciation and residual value, power purchase agreements, datacenter leases, capacity contracts, and equipment financing arrangements.
Analyze interest-rate sensitivity, refinancing requirements, maturity walls, covenant structures, and liquidity risks.
Develop downside and stress scenarios to assess how weaker demand, declining hardware values, delayed construction, power constraints, or tighter financial conditions could affect borrowers and lenders.
Track the migration of lending activity from regulated banks to nonbank financial institutions.
Assess how the growth of private credit and nonbank lending changes where financial risk is concentrated and how losses could spread during a downturn.
Produce flagship research reports and recurring coverage on AI infrastructure financing and credit markets.
Build proprietary datasets from bank reports, fund filings, corporate disclosures, securitization documents, loan agreements, and other financial sources.
Work closely with SemiAnalysis’s datacenter, semiconductor, energy, and supply chain teams to ensure financial analysis is grounded in what is physically being built, contracted, delivered, and energized.
Present research findings to clients and represent SemiAnalysis’s credit views through public writing, meetings, podcasts, conferences, and other industry discussions.