Associate Director – Infrastructure (Project Finance), Denver
S&P Global
- Location
- US - CO - ENGLEWOOD 15 INVERNESS WAY EAST
- Work model
- On-Site
- Level
- Senior
- Salary
- $120k – $148k/yr
- H-1B history
- 10 approvals (FY2023)
- Posted
- Sep 16, 2026
Skills
About this role
About the Role
Grade Level (for internal use): 12 The Team Credit Ratings is part of S&P Global's Global Ratings Services, bringing together more than 1,400 analysts across leading financial centers worldwide. The Infrastructure & Project Finance practice delivers credit analysis on essential, long-lived assets and ring-fenced project financings, covering contractual frameworks, demand and operating risks, sponsor strength, and financial resilience under stress. The North America Infrastructure Ratings team provides independent credit analysis and ratings on essential infrastructure assets and financings throughout the U.S. and Canada — spanning transportation, energy and utilities, digital infrastructure (including data centers), and social infrastructure — across both project finance structures (PPP/availability-based, contracted-revenue, and demand-risk) and corporate debt, including regulated Investor-Owned Utilities, midstream operators, LNG developers, and power generators. Supported by a strong pipeline of new issuances and refinancings, the team deliver s time ly , rigorous credit assessment, clear rating rationale, and ongoing surveillance, supporting capital formation and market understanding across rapidly evolving subsectors. Responsibilities and Impact Team Contribution & Capability Building Coach junior team members on credit fundamentals, modeling discipline, and the responsible use of AI tools, coordinating work across credits to manage quality and capacity risks. Embed continuous improvement into team routines by developing analytical playbooks, prompt libraries, and standard processes, and driving their adoption across the team. Core Analytical & Delivery Lead end-to-end credit analysis for an assigned portfolio of North America infrastructure project finance credits, preparing committee-ready materials and participating actively in rating committees. Manage portfolio surveillance and updates, connecting market developments and project performance to forward-looking risk themes, and embed AI tools into analytical workflows with disciplined validation and documentation. Stakeholder & Market Engagement Synthesize data, analysis, and research into clear, market-facing narratives for senior stakeholders and market participants, and contribute to thought leadership and sector commentaries. Risk Management and Operating Ensure adherence to analytical methodology, confidentiality standards, and data governance requirements, escalating risks early and contributing to controlled automation workflows with appropriate governance and human oversight. Compensation / Benefits Information US Candidates Only S&P Global states that the anticipated base salary range for this position is $120,000 to $148,000 USD. Final base salary for this role will be based on the individual's geographic location, as well as experience level, skill set, training, licenses, and certifications. In addition to base compensation, this role is eligible for an annual incentive plan. For more information on the benefits we provide to our employees, please visit spgbenefits.com/benefit-summaries.
What We're Looking For
Required Skills and Experience An S&P Global employee at this level would typically have 5+ years of relevant experience in project finance or infrastructure finance, including roles in ratings, banking, advisory, investing, or credit. Demonstrated understanding of infrastructure project structures and documentation, including PPP agreements, EPC and O&M contracts, and offtake or availability-payment frameworks. Demonstrated financial analysis skills, including cash flow modeling, ratio and covenant analysis, and accounting fundamentals. Demonstrated ability to deliver high-quality credit analysis across a portfolio with limited oversight and coach junior analysts through structured feedback and quality review. Practical experience embedding generative AI, large language models, or agentic workflows into analytical