Director, Infrastructure – Project Finance, New York

S&P Global•New York, NY

23h•Hybrid

About The Position

The Director will manage a diverse portfolio of North American infrastructure credits and deliver rigorous, forward-looking rating opinions across project finance and corporate debt. The role covers essential infrastructure assets and financings in the U.S. and Canada, including transportation, energy and utilities, digital infrastructure such as data centers, and social infrastructure. Relevant corporate debt coverage includes regulated investor-owned utilities, midstream operators, LNG developers, and power generators. The Director leads and develops analysts, drives analytical quality and consistency, and engages with issuers, investors, and other market participants. The role also advances analytical practices by incorporating generative AI, advanced analytics, and automation into research, monitoring, drafting, and workflows, while maintaining human judgment, transparency, validation, and accountability. Employees must work from the office at least two days per week, and final-stage candidates must attend at least one in-person interview. The position is limited to people with an indefinite right to work in the United States.

Requirements

Typically 10 or more years of relevant experience in project finance or infrastructure finance, including experience in ratings, banking, advisory, investing, or credit.
Understanding of infrastructure project structures and documentation, including PPP agreements, EPC and O&M contracts, and offtake or availability-payment frameworks.
Strong financial analysis expertise, including cash flow modeling, ratio and covenant analysis, and accounting fundamentals.
Ability to lead and deliver high-quality credit analysis across a wide variety of asset classes.
Ability to train and coach junior analysts through structured feedback and quality review.
Experience mentoring or managing analysts and building team capability and a culture of accountability and continuous improvement.
Practical experience using generative AI, advanced data analytics, or automation tools to improve research, monitoring, and workflow efficiency while maintaining validation and analytical discipline.
Strong relationship management and communication skills, including the ability to present complex analytical insights credibly to issuers, investors, and market participants while maintaining analytical independence.
Disciplined portfolio risk oversight, including the ability to identify emerging risks, escalate appropriately, and operate within governance frameworks.
Bachelor's degree or equivalent.
Indefinite right to work in the United States.

Nice To Haves

Master's degree.
Professional certification such as CFA.
Academic background supporting innovative and critical thinking.

Responsibilities

Manage a diverse portfolio of North American infrastructure credits and deliver forward-looking rating opinions.
Lead, coach, and develop analysts, including building credit expertise and capability with digital and AI-enabled tools.
Embed generative AI, advanced analytics, and automation into monitoring, drafting, research, and workflow execution while preserving human judgment and accountability.
Lead high-quality credit and capital markets analysis across assigned issuers and sectors for ratings, monitoring, risk assessments, and rating committee discussions.
Translate issuer and sector developments into clear analytical perspectives, incorporating scenario analysis and forward-looking risks.
Identify and implement workflow improvements with Data, Technology, Compliance, In-Business Control, and Methodology teams.
Build and maintain relationships with issuers, investors, and market participants through credible, insight-led engagement.
Communicate complex, data-informed analysis clearly while maintaining analytical independence and objectivity.
Ensure clear documentation, high-quality analytical outputs, and adherence to governance and regulatory standards.
Oversee portfolio risk, identify emerging risks, and escalate them early.
Maintain disciplined oversight of AI and automated outputs, including transparency, explainability, validation, and appropriate controls.