Senior Analyst, Infrastructure & Project Finance – Denver

S&P Global•Englewood, CO

1d•Hybrid

About The Position

The Senior Analyst, Infrastructure & Project Finance role is within S&P Global's Credit Ratings division, specifically the North America Infrastructure Ratings team. This team provides independent credit analysis and ratings on essential infrastructure assets and financings across the U.S. and Canada, including transportation, energy and utilities, digital infrastructure, and social infrastructure. The role supports capital formation for critical infrastructure assets by delivering rigorous credit analysis, clear rating rationale, and timely surveillance. The position involves applying AI and large language model tools within analytical workflows, coaching junior analysts, and engaging with clients and rating committees.

Requirements

3 to 5 years of relevant experience in project finance, infrastructure finance, or a related credit discipline such as ratings, banking, advisory, or investing.
Demonstrated ability to develop and support credit views, manage a portfolio of credits, and prepare committee-ready materials across North American infrastructure sectors.
Demonstrated ability to perform rigorous financial analysis, including cash flow modeling, ratio and covenant analysis, and application of accounting fundamentals to summarize key risks, mitigants, and sensitivities.
Effective written and verbal communication skills, including the ability to draft clear, high-quality rating reports and present structured analytical narratives to senior stakeholders and rating committees.
Demonstrated experience applying AI or large language model tools within analytical workflows, with the ability to validate outputs using sound credit judgment.
Bachelor's degree or equivalent required.

Nice To Haves

Experience covering North American infrastructure or project finance markets, with awareness of key sector developments including transportation, power, or digital infrastructure.
Demonstrated coaching or knowledge-sharing capability that supports consistent analytical standards across a team.
Experience contributing to internal knowledge-building initiatives, working groups, or research and commentary efforts.
Experience contributing to or designing automation or agentic workflows within a governed, controlled analytical environment.
A master's degree or professional certification (such as CFA) is highly valued.
Candidates from traditional finance disciplines as well as diverse academic backgrounds that support innovative and critical thinking.

Responsibilities

Coach Research Assistants and Rating Analysts on credit analysis, data discipline, and analytical tooling, building team capability through shared standards and repeatable analytical processes.
Identify and propose AI-enabled workflow improvements and lightweight automations that free team capacity for higher-value analysis, partnering with senior members and Data/Engineering teams to scale solutions with appropriate governance and controls.
Lead end-to-end credit analysis and ratings execution for assigned credits, owning surveillance and portfolio updates that synthesize performance data, market signals, and peer context into timely, committee-ready risk insights.
Prepare, review, and validate financial models, analytical inputs, and key outputs — including cash flow modeling, ratio and covenant analysis — ensuring alignment to methodology, sector frameworks, and evidentiary standards.
Apply AI and large language model tools within recurring analytical workflows, using structured validation and sound analytical judgment to maintain the quality and integrity of conclusions.
Participate in management meetings, due diligence calls, and surveillance discussions alongside senior team members, translating complex analysis into clear, structured narratives for clients and rating committees.
Build trusted stakeholder relationships through collaborative, analytically credible, and adaptable communication.
Ensure adherence to analytical methodology, confidentiality standards, and data governance requirements, escalating issues early with clear options and recommendations.
Contribute to the design, testing, and rollout of controlled automation and agentic workflows, including defining what must remain human-led, particularly for material risk calls and rating committee conclusions.